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GAMBER UNIV VERTICAL SURF MOUNT SML

Mfg # DS-138 CDW # 4729829 | UNSPSC 43212002

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This item was discontinued on March 15, 2023

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Gamber-Johnson Universal Vertical Base - mounting component is rated 4.40 out of 5 by 72.
Rated 5 out of 5 by from Data analytics solution where data can be coded and compressed and does not require additional infrastructure What is our primary use case? This solution is used as part of our data warehouse solution. We have some customer indexing content in this Vertica product. Vertica is a relational database that is used as part of our data warehouse implementation. What is most valuable? Vertica is a great product because customers can compress and code data. The infrastructure that data warehouse solutions need is a commodity server so that customers don't have to invest in infrastructure. Vertica is a column oriented database so the response of queries is very fast. What needs improvement? In a future release, we would like to have artificial intelligence capabilities like neural networks. Customers are demanding this type of analytics. For how long have I used the solution? We have been using this solution for six years. What do I think about the stability of the solution? This is a stable solution. What do I think about the scalability of the solution? This is a scalable solution. How are customer service and support? The customer service for this solution is good. How would you rate customer service and support? Neutral How was the initial setup? The initial setup is straightforward. What other advice do I have? It is important for those considering this solution to have some experience in database management solutions because Vertica is a relational database. Knowledge regarding SQL and any other database related skills is very important in order to implement or use this product correctly. I would rate this solution a nine out of ten. Disclaimer: My company has a business relationship with this vendor other than being a customer:Partner
Date published: 2022-11-13T00:00:00-05:00
Rated 5 out of 5 by from High performance database, low maintenance, and simple setup What is our primary use case? We are using Vertica for dashboards, storing, retrieving, and processing data. What is most valuable? The most valuable feature of Vertica is the unmatchable database performance at a fraction of cost compared to other similar databases. What needs improvement? Vertica can improve automation and documentation. For how long have I used the solution? I have been using Vertica for approximately seven years. What do I think about the stability of the solution? Vertica is stable. They have made improvements in this area but can still improve. What do I think about the scalability of the solution? The scalability of Vertica is good. We have approximately 100 users using this solution. How are customer service and support? The support from Vertica is good, they are knowledgeable. However, sometimes there are some challenges when escalating our issue. Which solution did I use previously and why did I switch? I have previously used Teradata long time ago. The price of Teradata was very high and hardware is vendor specific. Vertica can operate on comodity hardware and therefore easily scalable. How was the initial setup? The initial setup of Vertica is straightforward. What's my experience with pricing, setup cost, and licensing? The price of Vertica is less expensive than some competitors, such as Teradata. What other advice do I have? We require one person for maintenance for the 100 users we have. I rate Vertica an eight out of ten. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2022-11-01T00:00:00-04:00
Rated 5 out of 5 by from Powerful tool, excellent revision options, with easy depolyment What is our primary use case? The primary use case is machine learning and currently, I am working on IOT projects. How has it helped my organization? With Vertica, I am able to make changes using other Vertica features and I do not have to start the project over. The Vertica tool is very powerful but you cannot purchase the product based on individual features. What is most valuable? I am highly trained on Vertica and I am resistant to using other products because I do not have experience with those products. Some of the most valuable features are cybersecurity and backup. What needs improvement? The biggest problem is the cost of cloud deployment. For how long have I used the solution? I have worked with Vertica for the past five years. How was the initial setup? The initial setup is straightforward and easy deployment. What other advice do I have? I would rate Vertica an eight out of ten. Which deployment model are you using for this solution? Hybrid Cloud If public cloud, private cloud, or hybrid cloud, which cloud provider do you use? Other Disclaimer: My company has a business relationship with this vendor other than being a customer:Partner
Date published: 2022-11-20T00:00:00-05:00
Rated 5 out of 5 by from Most important feature is the fast database, but also has a lot of machine learning functions and integrations What is our primary use case? I'm a Vertica specialist, and I'm certified by Micro Focus. The solution is deployed on-premise, but we have another installation on the cloud for another client. What is most valuable? It's the fastest database I have ever tested. That's the most important feature of Vertica. It has a lot of contents and machine learning functions. Today we have a lot of options for deploying. It has a lot of integrations. What needs improvement? I think they need an easy client so that you can write queries easily, but it's not necessarily a weak point. I think some users would need them. In other versions of Vertica, there is a lack of integrations in some machine learning models. But today, the latest version has it all. I don't think they need too much improvement in that area. For me, it's great considering the use case I work with. For how long have I used the solution? I have been using this solution for four years. How are customer service and support? I haven't really had the opportunity to talk with them, but that's because the database just works. I don't really need technical support for maintaining and running the database. The documentation is very clear too. What's my experience with pricing, setup cost, and licensing? The pricing depends on the license model because there are several. It depends on the client, but it's cheaper than other solutions. I think it's cheap for all the functionality and robustness. It's not very expensive to deploy. What other advice do I have? I would rate this solution 8 out of 10. People should be careful with the way they are loading their data because Vertica is very fast at copying data. There are some operations that are slower than Oracle or SQL Server, but normally you wouldn't use that. Which deployment model are you using for this solution? On-premises Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2022-01-18T00:00:00-05:00
Rated 5 out of 5 by from Great performance, stable and easy to use database What is our primary use case? We hold financed data on the Vertica database, and clients use the data for reporting and other purposes. How has it helped my organization? Vertica provides benefits to our customers and helps with their performance. What is most valuable? The most valuable feature is Vertica's performance and the ease of using the database. Also, it is great for partnering with data. What needs improvement? We faced some challenges when trying to use the temporary tables feature. First, we installed Vertica on the AWS cloud and tried to read the data from Bitbucket to Vertica. We were able to read the data, but when we were trying to transform the data and load it into Vertica physical tables, we experienced performance issues. Regarding additional features, we are unsure if Vertica has updated its features, but we've experienced difficulty in integrating with third-party tools. Clients use multiple technologies and value that integration. Sharing data with third parties should also be improved. For how long have I used the solution? We have been using this solution for two years and are using the latest version. What do I think about the stability of the solution? It is a stable solution. What do I think about the scalability of the solution? It is a scalable solution. Initially, we had issues with the scalability, but with the new version, Vertica resolved the issues. Regarding how many users are using this solution, I do not have a specific number, but our organization is large. So, for example, in a unit with about fifteen clients, two to three clients use Vertica. What other advice do I have? I rate this solution a seven out of ten. Snowflake claims to have many more features than Vertica, but we cannot compare both solutions as we have not used Snowflake. However, if Vertica integrates the use of third-party tools, it would be great and more competitive. Which deployment model are you using for this solution? Public Cloud If public cloud, private cloud, or hybrid cloud, which cloud provider do you use? Amazon Web Services (AWS) Disclaimer: My company has a business relationship with this vendor other than being a customer:Partner
Date published: 2022-07-20T00:00:00-04:00
Rated 5 out of 5 by from Scalable big data analytics platform that is reasonably priced compared to other solutions What is our primary use case? Our primary use case for this solution is data analytics. What is most valuable? The hardware usage and speed has been the most valuable feature of this solution. It is very fast and has saved us a lot of money. What needs improvement? The integration of this solution with ODI could be improved. For how long have I used the solution? I have used this solution for 1 year. What do I think about the stability of the solution? This is a stable solution with a fast compression system. What do I think about the scalability of the solution? This is a scalable solution. How are customer service and support? The technical support for this solution is really good. The support team are friendly and provide assistance quickly. How would you rate customer service and support? Positive How was the initial setup? The initial setup is straightforward. What's my experience with pricing, setup cost, and licensing? The pricing for this solution is very reasonable compared to other vendors. What other advice do I have? I would rate this solution a ten out of ten. Which deployment model are you using for this solution? On-premises Disclaimer: My company has a business relationship with this vendor other than being a customer:partner
Date published: 2022-04-15T00:00:00-04:00
Rated 5 out of 5 by from Useful large aggregations, beneficial subclusters, but scalability could improve What is our primary use case? I am using Vertica for aggregations and dashboards. What is most valuable? The most valuable feature of Vertica is the ability to receive large aggregations at a very quick pace. The use case of subclusters is very good. For how long have I used the solution? I have been using Vertica for three and a half years. What do I think about the stability of the solution? Over the last few months with the new release of Vertica, there have been stability problems. The performance should improve. What do I think about the scalability of the solution? Vertica seems to scale well, except for one use case where you are on a multi-node cluster. For example, if you had a nine-node cluster, one node goes down, then the eight nodes don't scale, because the absence of the node is very apparent, which is a problem. If you have nine nodes or multiple nodes, the whole idea is that if one of those nodes goes down, then you should not see an impact on the system if you have enough capacity. Even though we have enough capacity, you can still see the impact of the one node going down. We have approximately 25 people using this solution in my company. Most of the users are developers. We have been increasing usage of the solution. How are customer service and support? The technical support from Vertica is good, but the fixes take a long time if there is a problem. I rate the support of Vertica a three out of five. Which solution did I use previously and why did I switch? I have not used another similar solution to Vertica. What about the implementation team? We had assistance from Vertica with the implementation of the solution. What other advice do I have? I would advise others to try the solution out. I rate Vertica a seven out of ten. Which deployment model are you using for this solution? Public Cloud If public cloud, private cloud, or hybrid cloud, which cloud provider do you use? Amazon Web Services (AWS) Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2022-06-29T00:00:00-04:00
Rated 5 out of 5 by from A scalable unified analytics platform with good performance What is our primary use case? Our use case is a typical data warehouse. We just use the data warehouse for reporting and the storage of data. Our users are the staff team who do the reporting and data analysis. What is most valuable? The feature I like best is performance. We use Red Tool and Red Job for the data warehouse and reporting. It's perfect. Performance is good, and it can return ad hoc queries very quickly. Of course, it's a cluster, so it's easy to scale. What needs improvement? It's hard to make it slow for a small data volume. For large volumes, it's hard to make it work. It's also hard to make it faster, and to make it scale. For how long have I used the solution? I have been using Vertica for about five years. What do I think about the stability of the solution? It's a stable solution. What do I think about the scalability of the solution? Vertica is a scalable solution. How are customer service and technical support? Technical support is good, and they react quickly. How was the initial setup? The initial setup is okay. You will need some knowledge and some training. I'd say learning takes a couple of months. We use one person to maintain the database side. With the DevOps team, everyone has a different role. But for our database, it's just one person. What's my experience with pricing, setup cost, and licensing? The price is reasonable. We use a pay per license model. Firstly, you need to buy a license. After that, you mainly pay the annual support fee of around 20% or 25%. I think their prices are quite reasonable. What other advice do I have? We tried to use data lake kind of stuff for machine learning, but for the key functionality of the data warehouse, it's great. Personally, I feel they are over-marketing the machine learning feature and for something like the semi-structured data. But for the data warehouse, it's truly a good solution. I want to recommend it highly. I would tell potential users that it's hard to make it slow for small data volumes. For large volumes, it's hard to make it work, make it faster, and make it scale. Depending on your workload and your use case, you need to first purchase the Red Tool. After that, you need to follow the best practices to have an efficient design. On a scale from one to ten, I would give Vertica a nine. Which deployment model are you using for this solution? On-premises Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2021-06-24T00:00:00-04:00
Rated 5 out of 5 by from Extremely fast query performance, effective real-time API integrations, and highly qualified support What is our primary use case? We are using Vertica for our data warehouse. We run all the ETL and then store the information for the reports which are given to the business team for use for analytical purposes. What is most valuable? Vertica is a columnar database where the query performance is extremely fast and it can be used for real-time integrations for API and other applications. The solution requires zero maintenance which is helpful. What needs improvement? They could improve the integration and some of the features in the cloud version. For how long have I used the solution? I have been using Vertica for approximately six years. What do I think about the stability of the solution? The solution is highly stable. We have approximately 15 users using this solution in my organization. What do I think about the scalability of the solution? Vertica is scalable. How are customer service and technical support? The support is extremely good, they respond immediately and are highly qualified. We interact with them once in a while to have new features explained, sessions understanding, and if we have an issue. We have a good relationship with them. How was the initial setup? The installation is not simple, if you go through the documents that are provided you should manage to do it. However, having some technical knowledge would be recommended. The time it took to do the implementation was approximately 45 minutes. There is additional software or features that we needed to deploy as part of the migration. What about the implementation team? We did the implementation ourselves with a five-person technical team. However, the first time we did the implementation we had support from the Vertica team. They helped us by providing recommendations and best implementation practices. What's my experience with pricing, setup cost, and licensing? The pricing could improve, it is a little expensive. Which other solutions did I evaluate? I have evaluated Postgres. What other advice do I have? I would recommend this solution to others if it fits their use case. If someone is looking for a data warehouse solution with a fast query process Vertica is a good choice. However, it is different than a relational database. If the choice was between Postgres and Vertica, I would recommend Vertica. I rate Vertica nine out of ten. Which deployment model are you using for this solution? Hybrid Cloud Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2021-09-23T00:00:00-04:00
Rated 5 out of 5 by from User-friendly, stable, and scalable What is our primary use case? We use the solution in our data warehouse. What is most valuable? The solution is quick, has good compression data, and is not expensive. Vertica is user-friendly. What needs improvement? The integration with AI has room for improvement. There is room for better machine learning. For how long have I used the solution? I have been using the solution for 16 years. What do I think about the stability of the solution? The solution is stable. What do I think about the scalability of the solution? The solution is easy to scale. We have seven people using the solution. How are customer service and support? The technical support is good. How was the initial setup? The initial setup is straightforward. The deployment took four days. What about the implementation team? The implementation was completed by a vendor. What's my experience with pricing, setup cost, and licensing? The price is reasonable. The solution is free and we pay for the storage. What other advice do I have? I give the solution a nine out of ten. Which deployment model are you using for this solution? On-premises Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2023-03-22T00:00:00-04:00
Rated 5 out of 5 by from Features valuable to me include: massive data ingestion performance and SQL standard query engine. Valuable Features: * Massive data ingestion performance * Performance * SQL standard query engine Improvements to My Organization: DWH core platform is based on it Room for Improvement: * Machine learning implementations * Support for Cloud based environments like Google Compute Engine ( https://www.itcentralstation.com/products/google-compute-engine ) Use of Solution: 3 years Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-08-31T00:00:00-04:00
Rated 5 out of 5 by from The Workload Analyzer helps you easily to analyze your database workloads and recommends tuning opportunities to maximize the database performance. Valuable Features Storage abstraction through projections. It gives you the possibility to react to any kind of query with an optimal performance. The Workload Analyzer helps you easily to analyze your database workloads and recommends tuning opportunities to maximize the database performance. This in turn reduces your operational costs. I love the hybrid storage model and due to that the full control of load and query behavior. I also like the ability to read semistructured data with FlexTables for DataExploration. Improvements to My Organization We are now able to procde real-time insights into our tracking data, and with that show how our customers are using the products that we have. Furthermore, it is now possible for our Data Science department to easily, and quickly train their new data mining models and get answers faster than ever before. With the hybrid storage model along with well designed resource pools and storage abstraction through projections, we are now able to easily load new data constantly throughout the whole day. While doing this, we can still be available to perform data analytics on new and legacy data quickly, and even Microstrategy for enterprise reporting doesn’t need to cache data. Most reports can be generated with live queries and still finish within seconds. So in a nutshell: - Faster Information Insight (Data to Insight cycle) - Less complexity on data modeling - Less operational costs Room for Improvement I would love to see direct connections to other DMSs. Something like a direct connector to Oracle, MySQL, MS SQL, MongoDB, etc. so that you can copy data between Vertica and other vendors directly and more easily without an ETL tool, dump, transport, or load data. Use of Solution I've been using Vertica for two and a half years. Scalability Issues We had an issue caused by adding nodes, but this error was caused by ourselves, as we didn’t use the proper process for adding nodes. That led to some problems that needed to be solved. Even though we did something bad, the instance was still working properly from an outside point of view. Customer Service and Technical Support We had to contact support for the above mentioned issues with adding nodes, and some other minor questions. All pf our questions were been answered in an appropriate time, and for the complicated problem we needed to solve, we were provided a direct contact and solved this during a conference call with a technician from Boston. So all in all, I would rate the customer service and technical support team from HPE Vertica as one of the best. Initial Setup The documentation and install procedures cannot be any more straightforward. You get all the information you need from the documentation in a well structured form. We also got support from Vertica for the first setup. They made hardware configuration suggestions and involved us in any details to help us to understand the overall process. During installation, the scripts were check numerous hardware and software settings to help you achieve the best performance for your environment. Implementation Team We implemented our first cluster in collaboration with the HPE Vertica team. I would always suggest this step, as you will be able to better understand the details about Vertica and how to operate the system efficiently. Pricing, Setup Cost and Licensing My advice for pricing/licensing/ROI in a "proprietary proprietary“ comparison. You won’t achieve a better cost effectiveness with a different vendor. Other Solutions Considered We did a PoC between competitors and Vertica. Throughout the whole PoC, Vertica performed much better in terms of its stability, flexibility, performance and ease of use. We didn’t encounter any problems or downsides, and it didn’t matter what we tested. At that stage, just the Management Console had some minor issues, but even those are now fixed and are not important for the core database engine. I would name HPE Vertica as the most mature columnar database with a best of class data storage and query engine. Other Advice From the beginning, work closely with HPE Vertica. There's a great Vertica community and a great network to many other companies in the world using this system. Vertica is the most flexible columnar storage with an outstanding performance for any kind of situation. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-06-24T00:00:00-04:00
Rated 5 out of 5 by from We built a custom analytical tools on top of Vertica. Valuable Features * HA Clustering * Speed / Performance Improvements to My Organization We're able to retrieve queries nearly instantaneous for our custom analytical tools we built on top of Vertica. Room for Improvement More frequent updates. Use of Solution 1 year Stability Issues None. Scalability Issues None. Customer Service and Technical Support Very knowledgable team which has provided excellent documentation for every issue we've had to troubleshoot. Previous Solutions MonetDB -- unstable, frequent crashes. Initial Setup Straightforward, was able to get the database up fairly quickly with minimal effort. Pricing, Setup Cost and Licensing We're still using the Community Edition (CE). Other Solutions Considered MonetDB, Cassandra, Amazon RedShift. Other Advice Great product, very mature and robust. Vertica is able to scale to meet our demands as we scale our business 10x. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-10-30T00:00:00-04:00
Rated 5 out of 5 by from The ability to view running queries and cancel problem ones from the Management Console is a very nice feature. Primary Use Case Vertica is our sole data warehouse solution. It is our single point of access to all data loaded from disparate data sources across the organization, and is the single point of truth for all business rules encapsulated in our fact and dimension tables. All of our reporting to all business departments originates from Vertica. We are also using Vertica's inherent analytic functions, most notably geospatial, and are automating much of our analytics team's R libraries and functions into Vertica for faster processing. Improvements to My Organization The fast columnar store database structure allows our query times to be at least 10x faster than on any other database. This enables us to get answers to data questions as well as numerous analytics on our data out to our internal and external clients quickly. We are able to integrate our Vertica data warehouse with Tableau to create numerous reports quickly and efficiently. What was once a two year backlog of report requests on our old data system has been virtually eliminated now that we are using Vertica to provide the solutions. We are able to create complex reports in Tableau by crunching the data in Vertica first and simply extracting the data to Tableau. We have used Vertica to automate manual processes across our business that previously used mostly Excel, and now R, improving efficiency company-wide. We have saved our Analytics Department days worth of man hours each month by using Vertica's Integrated R package instead of their local R Studio implementations. We are also opening new areas of business and potential new revenue streams using Vertica's analytic functions, most notably geospatial, where we are able to run billions of comparisons of lat/long point locations against polygon and point/radius locations in seconds. Valuable Features I have found great use out of many features, most notably the Management Console and the Database Designer. Many people with lots of experience creating table projections can get frustrated trying to optimize some complex queries, however, in Vertica, the Database Designer is normally a big help in these situations. You can feed it your problem queries and it will make projection design suggestions for you. The ability to have multiple projections on a table to work with different queries is a big bonus. The Management Console is an invaluable tool for monitoring the health of our Production and DR clusters. Copy Cluster and Cluster Replication help us keep both easily in sync on a daily basis. Integrated R and geospatial functions are helping us improve efficiency and explore new revenue streams. Room for Improvement Documentation has become much better, but can always use some improvement. Love the tech support, but hoping Micro Focus will invest in some additional training for the Level 1 responders so they are much more familiar with more areas of the product. Use of Solution More than five years. Stability Issues Our system is very stable. In the two years I have administered Vertica at this job, I have had 100% uptime outside of planned outages for upgrades and hotfix applications. Scalability Issues No issues. Amazingly scalable. Adding one node was very easy, as was adding memory to all nodes. We are currently in the process of setting up a Dev / DR environment which is going very smoothly. Customer Service and Technical Support Customer Service: I have a great relationship with Vertica customer support. They are friendly, knowledgeable, and are quick to respond. Technical Support: HPE Professional Services have also been a huge help to us when needed. They are well worth the investment. It is extremely rare that I ever have an issue with Technical Support. My requests are always given a very quick initial response. Almost always get rapid feedback on my issues, and immediate escalation to the appropriate engineering team, either upon request or when the first level support rep needs additional insights on their own. On rare occasion, I have gotten a rep who is likely newer and almost reading off the script, but I am always able to give them enough info upfront so they avoid most of that, and they accommodate my escalation requests, if necessary. Previous Solutions No, not at this company. At my last company, we initially used Aster Data (now owned by Teradata). Once our database grew too large, it was unable to handle the number of transactions we were completing per day. Many queries on our largest table were taking from 20 minutes to over an hour to complete. Right out of the box, our longest queries went down to under a minute, most completing in a matter of seconds. Initial Setup The initial setup was straightforward. We used an HPE-affiliated vendor to purchase and properly set up the equipment, completed a PoC, and then we had HPE Professional Services assist with the transition from our old system to Vertica. Our Linux team loves it as one of the best installation packages. Initiate on one node, and the RPM propagates automatically to all other nodes. Implementation Team We implemented through a vendor. I highly recommend using IIS, they are amazing. I do all business through IIS. Top notch vendor, they are not just a "call and send a quote" company. I have developed a great professional relationship with my reps over the last five years over two Vertica admin jobs. They come onsite, enable access to the highest levels of Vertica engineering and management when needed, and also have found us opportunities at many of Vertica/HPE/Micro Focus trusted partners, such as Docker and Ormuco. Pricing, Setup Cost and Licensing The pricing, based on raw TB of data stored, is fair and affordable. You can have multiple projections per table without incurring a cost beyond the initial data load. The fact that a Dev and a DR cluster are included in the license cost is a great value! Work with a vendor, if possible, and take advantage of more aggressive discounts at mid-fiscal year (April) and fiscal year-end (October). Other Solutions Considered We evaluated Vertica and Greenplum, and chose Vertica due to cost and a number of existing use cases that were nearly identical to ours. Other Advice My only advice is to seriously consider using Vertica for your data warehouse needs. I have normally just gone with the flow and learned whatever tools our company chose. When we switched from Aster Data to Vertica, I made the initial recommendation to do so. I am so happy with this product that I am now an HP ASE Certified Vertica Administrator, and moved to a new job that is also using Vertica. I would not have changed jobs if I were not able to continue using this product. I am also recommending to management that we purchase HPE IDOL for our upcoming audio and video analytics needs. HPE Big Data Solutions is a great product suite, and I have bet my career on its future growth. I can't recommend Vertica highly enough. While no solution is perfect, Vertica offered the most right out-of-the-box, and continues to expand on its offerings with every release. I am looking forward to see what changes come as a result of the Micro Focus spin merger. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-06-23T00:00:00-04:00
Rated 5 out of 5 by from We thought the Management Console was a nice feature, but it turns out it gives us insight on what is happening behind the scenes. Valuable Features Speed of query response time for complicated queries on tables with billions of rows including joins on varchar columns. There is no limitation on which columns can be queried or joined on and we see query times in the milliseconds for a lot of queries that just won't return at all from other products. Ease of administration. The Management Console we thought was a nice to have turns out to give us insight on what is happening behind the scenes so easily it has sped up query tuning, insight as to what jobs are running, and resource use on the boxes the product sits on. Style of deployment. We were able to build out a server farm exactly as we are accustomed to. We did not have to buy fancy hardware. Our first cluster was deployed on servers we had sitting around from other migrations and replaced products. As we grow also the growth is native to how we do business. Improvements to My Organization We can have insight into data we never had before. We can provide that insight to internal users so we do not have to generate reports for them all the time. With response times like these there is no concern of having them wait for results to return and so they do not think things are broken. Room for Improvement Getting the Management Console up and running as expected was a bit of a challenge. Use of Solution We've been using it for one and a half years. Stability Issues We have amazing stability. We even had to migrate the databases to other boxes and found it moved the data without much intervention from us and no down time. It worked exactly as a cluster should. We joke here all the time that we would love to say we like Vertica support but since we never need them, we actually do not know! Scalability Issues Scalability is one of the huge strengths of this product, and scalable in a way, as I said before, that is native to how we do business. Customer Service and Technical Support We've never had to contact them. Previous Solutions We switched off of Infobright because it was not performant at all at the scale we needed. The number of limitations on Infobright are too many to list in a small review like this. Initial Setup Initial setup of the database was straightforward. Implementation Team We did need support though for the initial installation. They were incredibly responsive and helpful and deployment was completed in a very reasonable amount of time despite issues initially getting the Management Console up and running. Pricing, Setup Cost and Licensing Pricing is more than fair. This is very reasonably priced and since it is a perpetual license you are not stuck paying it again and again. Other Solutions Considered We evaluated Netezza and Teradata alongside Vertica. Other Advice Do you want to stand up a data warehouse in a reasonable amount of time using the in-house skills accustomed to dealing with an RDBMS? If that is the case, nothing beats Vertica, hands down. Disclaimer: IT Central Station contacted the reviewer to collect the review and to validate authenticity. The reviewer was referred by the vendor, but the review is not subject to editing or approval by the vendor.
Date published: 2016-05-31T00:00:00-04:00
Rated 5 out of 5 by from It leverages machine learning and predictive analytic features to help preprocess data What is our primary use case? The primary use case is as an analytics database on EC2 instances. How has it helped my organization? * We gain insights into data in real-time with blazing, fast SQL analytics across exabytes of data. * It maximizes cloud economics with Eon Mode by scaling cluster size to meet variable workload demands. * It leverages machine learning and predictive analytic features to help preprocess data. What is most valuable? It maximize cloud economics for mission-critical big data analytical initiatives. What needs improvement? It needs integration with multiple clouds. For how long have I used the solution? One to three years. What do I think about the stability of the solution? I have implemented it on Amazon EC2 instances with medium IT workloads. What do I think about the scalability of the solution? It has an elastic scalability solution. How was the initial setup? It is easy to integrate with EC2 instances. What's my experience with pricing, setup cost, and licensing? It is fast to purchase through the AWS Marketplace. The pricing and licensing depend on the size of your environment and the zone where you want to implement. What other advice do I have? It is a complete solution and a also good solution for EC2 instances. I have not tried to integrate it with other products. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2019-01-14T00:00:00-05:00
Rated 5 out of 5 by from The concurrency got better in this version and we are able to run more queries and load concurrently. Valuable Features The compute and processing engine returns the queries fast and let us use our analysis resources in a better utilization. The concurrency got better in this version and we are able to run more queries and load concurrently. Improvements to My Organization We built an internal dashboard using the MicroStrategy ( https://www.itcentralstation.com/products/microstrategy )to increase visibility to our management and our employees. Also, we built tool to expose the data to our selected partners and users to create better engagement with our platform. Room for Improvement * Loading times for “real time” sources - for example, loading from Spark creates a load on the DB at high scale * Connectors to other sources such as Kafka or AWS Kinesis * Better monitoring tools * Better integration with cloud providers - we were missing some documentation regarding running Vertica on AWS Use of Solution We've been using Vertica ( https://www.itcentralstation.com/products/hpe-vertica ) for a year. Stability Issues In case of one HD failure in the cluster, the entire cluster got slower. We feel that it should be able to handle such issues. Scalability Issues No. Customer Service and Technical Support The support was slow and didn’t provide a solution in most cases. The community proved to be the better source for knowledge and problem solving. Initial Setup Pretty straightforward, the installation was simple and we added more nodes easily as we grew. Pricing, Setup Cost and Licensing Vertica is pretty expensive, take into account the servers and network costs before committing. Other Solutions Considered We evaluated both AWS Redshift and Google BigQuery. Redshift didn’t fulfill our expectations regarding query latency at high scale (over 60 TB). Regarding BigQuery, we found the pricing structure pretty complex (payment per query and data processed) and harder to control. Other Advice Don't plan a production usage on high-scale straight on Vertica, use caching or other buffers between the users and the DB. Get yourself familiar with the DB architecture before planing your model (specifically, make sure you know ROS/WOS and projections). Try to avoid LAP before your schema gets stabilized. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-10-30T00:00:00-04:00
Rated 5 out of 5 by from We were able to implement new algorithms without having to move data out of Vertica into a compute cluster. Valuable Features User Defined Extensions Analytic Functions Improvements to My Organization We were able to implement new algorithms without having to move data out of Vertica into a compute cluster. This allowed us to offer Analytics for Cybersecurity to our customers. Room for Improvement More Machine Learning algorithms--Random Forest for sure! Customer Service and Technical Support Customer Service: Very responsive Technical Support: Excellent Implementation Team In-house Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-09-01T00:00:00-04:00
Rated 5 out of 5 by from You don’t have to worry about “load time slots” since you can load data into reporting tables at all times without worrying about their query load. Valuable Features It provides very fast query performance after good designs of projections. It's easy to implement for 24/7 data load and usage because you don’t have to worry about “load time slots” since you can load data into reporting tables at all times without worrying about their query load. It just keeps up and running all the time. Improvements to My Organization We have been able to move from nightly batch loads to continuous data flow and usage. This hasn’t happened just because of Vertica, we have renewed our data platform pretty thoroughly, but definitely Vertica is one major part of our new data platform. Room for Improvement We are running our data transformations as an ELT process inside Vertica; we have data at least on the landing area, temporary staging area, and final data model. Data transformations require lots of deletes and updates (which are actually delete/insets in Vertica). Delete in Vertica doesn’t actually delete data from tables, it just marks them as deleted. For us to keep the performance up, purge procedures are needed and a good delete strategy needs to be designed and implemented. This can be time consuming and is a hard task to complete, so more ‘out-of-the-box’ delete strategies would be a nice improvement. Use of Solution We've been using it since January 2015. Deployment Issues We haven't had any issues with the deployment. Stability Issues Stability is good, however the database crashed once because a query ran against a large XML data element. Scalability Issues We haven’t yet scaled out our system. So far performance has been good (taking into consideration that delete strategy mentioned in the Areas for Improvement question). Customer Service and Technical Support We haven’t needed tech support too much. So far so good. Previous Solutions We used Oracle for our DWH. When selecting a new database, we evaluated -- based both on written documentation and hands-on experimenting -- quite a lot of databases, such as Exadata, Teradata, and IBM Netezza. We selected HP Vertica as it runs on bulk hardware since it has “open interfaces”. It performed really well during hands-on experimenting and its “theories in practice” is good. Performance is excellent, development is easy (however, you need to re-think some things that you may have gotten used to when using other SQL databases), and its license model is simple. Initial Setup It seemed to be very straightforward. However, we had an experienced consult to do the setup. Implementation Team We had a joint team consisting of both an in-house team and external consultants. It’s very important to build up the internal knowledge by participating in actual project work. ROI We have ran so little time in production that we don’t yet have a decent ROI or other calculations done. Pricing, Setup Cost and Licensing The license model of HP Vertica is simple and transparent. Other Advice Just go for it and try it out; you can download the free Community edition from the HP Vertica website. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-03-31T00:00:00-04:00
Rated 5 out of 5 by from We switched from our previous solution because SQL Server did not scale. Valuable Features Geospatial Room for Improvement Profiling, query optimize, management. Use of Solution 1 year Deployment Issues Some bugs, they were rapidly fixed. Stability Issues Minute Scalability Issues Not yet Customer Service and Technical Support Customer Service: Excellent Technical Support: Very good Previous Solutions SQL Server ( https://www.itcentralstation.com/products/sql-server ) did not scale. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-09-01T00:00:00-04:00
Rated 5 out of 5 by from Ad-hoc data analysis improved the SLAs for our end clients. What is most valuable? The most valuable feature in the solution is ad hoc data analysis. It improved the SLAs for our end clients. What needs improvement? There are some predictive analytics features that we might be using which we thought were part of IDOL, but it seems some are also already part of Vertica. What do I think about the stability of the solution? The stability is super good, especially when you scale out. What do I think about the scalability of the solution? Before using Vertica, we used to have problems scaling out because we increase our customer base significantly each year. We have more than 20.000 clients now. Since we implemented the Vertica solution, it is much less effort to maintain scalability. How is customer service and technical support? I haven’t used technical support, but the IT colleagues definitely have. I think they are rather happy with it. I haven't heard any complaints. It could be quicker sometimes, but that's always the case with big processes. Which solutions did we use previously? Previously, we were basically using an old school setup based on a relational database. I’m not sure which database management system it was. The performance of the previous solution was no longer adequate to support the growth we were seeing in our business. Response times were up to 10-15 seconds on different queries. We needed to get that down to under a second. Now we’ve moved to a real big data analytics solution. How was the initial setup? I wasn’t involved with that, but I think that those who did it were happy with the support. What other advice do I have? When we chose a solution, we were looking at scalability, maintenance, and ease of use. With Vertica, we can access big data using regular SQL queries. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2017-01-22T00:00:00-05:00
Rated 5 out of 5 by from Having the ability invoke analytic functions without having write self join SQL statements is beneficial. Valuable Features: Analytic functions. Improvements to My Organization: We are trying to data mine customer event data. Having the ability invoke analytic functions without having write self join SQL statements ... just brilliant. Room for Improvement: Ability to use analytic functions in where clauses, being able to use aliases in the where and order by clauses will make query writing/reading a lot easier. Use of Solution: 2 years. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-09-01T00:00:00-04:00
Rated 5 out of 5 by from It's pretty straightforward to get the cluster up and running. Valuable Features * Speed * Parallelization * SQL language * High Availability Improvements to My Organization I have seen queries that take over 24 hours on MS SQL Server to complete, complete in less than 10 minutes on Vertica. I have seen queries that take several minutes, up to an hour, on MS SQL Server, complete in less than 10 seconds, sometime less than one second on Vertica. That allows analysts to spend their time analyzing results instead of waiting for results. Certain types of analysis weren’t even possible before, simply because it took too long. Room for Improvement While the documentation is very extensive and relatively complete, it’s poorly organized and there are way too few examples. It’s come a long way since the first version I saw, but it still has a long way to go. Plus, there is very little information on the internet. I can find a solution to nearly any MS SQL Server problem using Google. Not so for Vertica. Use of Solution I've been using it for five years. I started with version 4, which was prior to the HP acquisition. Deployment Issues It’s a breeze to setup if you’re using hardware and an OS that meet the minimum requirements. If you try straying from the recommendations, you can find yourself in trouble. Stability Issues If your queries and projections are optimized properly, it’s rare that you’ll run into stability issues. Stability issues are usually caused by improperly configured hardware/OS, or poorly written queries/projections. Scalability Issues Scalability is great if you size it correctly to start with. Resizing a cluster isn’t for the faint of heart. All the data needs to be redistributed across the cluster when the cluster size changes, and that can take a very long time, depending on how much data you’re storing. Customer Service and Technical Support The technical support for Vertica specifically is great. They still have lots of the original (pre-HP acquisition) support people working there who know the product inside and out. Initial Setup It's pretty straightforward to get the cluster up and running - assuming you follow the vendor recommendations closely. Getting your data in, setting up projections, optimizing queries, etc. is not as straightforward. If you’ve never used it before, save yourself hours of frustration and hire a Vertica consultant. Implementation Team The first time I used Vertica, we tried doing it ourselves in the beginning. We learned a lot from our failures, but still weren’t getting the results we’d hoped for. After getting professional services help, we were pointed in the right direction, and that made a world of difference. I highly recommend bringing in someone who knows what they’re doing to get you started on the right foot. Pricing, Setup Cost and Licensing It’s expensive, but it’s good once you get it working properly. Like any complicated software product, you’re paying for years of research and development, support, etc. Everyone’s use case is different, and sometimes it’s difficult to put a price on speed. You pay for the storage, not the number of processors or nodes. They have a community edition that allows up to three nodes with up to one TB of storage. You can try it out for free that way, and once you realize how well it works, you can purchase a commercial license as your storage footprint grows. Other Solutions Considered At a previous company, we looked at Greenplum as an alternative to Vertica. For our specific use-case, Vertica won the majority of our benchmark tests. If we had a design that required lots of updates and deletes, we may have compromised and gone with Greenplum. Other Advice How useful it is depends upon your use case. It’s not a be-all and end-all solution, and it’s great for data that doesn’t change. If you have massive fact and dimension tables, and you need to do analytics on them, this is the Cadillac. If you’re trying to replace your OLTP system, there are better suited solutions out there. These days, there are lots of alternative solutions in the big data space. Open source vs. Commercial. Every imaginable use case. Just like any project, there is the right tool for the job, but you don’t always know what tools are available. You end up using something because it worked before on a different job, or it’s the cheapest solution. Your best bet is always to closely determine your requirements, then find the best match. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-06-23T00:00:00-04:00
Rated 5 out of 5 by from Easy to implement, by tuning the model (projection design) you get great performance How has it helped my organization? It enabled delivery of a new Agile Data Warehousing Service. It enabled us to close large deals. Customers with large data sets had to be migrated from PostgreSQL to Vertica due to performance. What is most valuable? * Clustered database * Horizontal scaling * Disaster recovery * Columnar Storage * Compression (you read only columns you need) * Immutable storage * Fast ingesting What needs improvement? Performance of management of metadata layer (database catalog) needs improvement. We still have to have smaller customers on PostgreSQL; Vertica cannot manage thousands of schemata. Query performance: Improve either Database Designer (automation of projection design) or performance of queries using suboptimal projection design. Scaling of execution independently on storage: Upcoming Eon Mode (now Beta in Amazon) will hopefully solves this. For how long have I used the solution? One to three years. What do I think about the stability of the solution? Encountered stability issues three times during last three years. What do I think about the scalability of the solution? Suboptimal projection design causes queries to not scale linearly. The metadata layer does not scale linearly. Metadata for database files scale okay, but metadata related to tables/columns/sequences must be stored on all nodes. How is customer service and technical support? I have experience with legacy vendors of enterprise RDBMS solutions, and I rate Vertica support to be much better. Which solutions did we use previously? In my current company I was not responsible for the switch. As far as I know, they switched from PostgreSQL, especially because of performance of analytical queries processing large data. How was the initial setup? Just getting Vertica running is straightforward. However, with an increasing number of customers, we had to develop our own tooling. For example: * Automated deployment * Monitoring, alerting * Backup/restore. What's my experience with pricing, setup cost, and licensing? Start with license per 1TB. Starting from hundreds of TB there is unlimited licensing to be considered. Move historical data to HDFS/S3 which are significantly cheaper or even free. Vertica is delivering more and more features to support load/unload for external storages. Which other solutions did I evaluate? 2012 - Detailed evaluation including benchmarks of: Greenplum, Vectorwise. 2017 - Evaluation of features and initial communication with vendors, if needed, for: Greenplum, EXASOL, Amazon Redshift, Spark, SAP HANA, IBM dashDB, Snowflake, Azure SQL. What other advice do I have? It is easy to implement this solution for one customer. By tuning the model (projection design) you get incredible performance. You won’t face issues with metadata (catalog) layer up to tens of thousands of tables. It can be a challenge to operate clusters for many customers with varied data pipelines. Consider using Database Designer. Don't hesitate to push Vertica (through support/product management) to improve it. Consider implementing your own tools to automate performance tuning tasks. Disclaimer: My company has a business relationship with this vendor other than being a customer:Partner.
Date published: 2018-01-17T00:00:00-05:00
Rated 5 out of 5 by from Its speed differentiates it from other columnars, and works on commodity hardware What is our primary use case? When I have a business need for a few pieces of information, and I need to process it quickly, that's when I use Vertica. How has it helped my organization? We got something like a six-times improvement using Vertica. What is most valuable? The feature of the product that is most important is the speed. I needed a columnar database, and its speed is what it's built to do, and so that's what really does differentiate Vertica from its competitors. I think what also draws me to it is that I don't need any special hardware. So I can use commodity hardware, which is nice to have in a commercial solution. What needs improvement? I think it's starting to get a little expensive. Open source products are starting to get more robust, so I think that's something that they need to start looking at in terms of licensing. For how long have I used the solution? More than five years. What do I think about the stability of the solution? Absolutely stable. It's supported. The stability is one thing, the support is the other thing. What do I think about the scalability of the solution? No scalability issues. Like I said, in its competitive set it is just faster, better, depending on how you use it, because it is columnar. How is customer service and technical support? We don't need them that much, but when we do need them, we use the virtual tech support, and that's fine. It works, and it's responsive. Within 24 hours, we get resolution. We didn't pay for a higher tier of service, but we generally just have questions for support. Which solutions did we use previously? We've used Greenplum, Teradata, and then Vertica. We used the big data open source solutions as well that are getting better. So those are the four that I can think of off the top of my head. Greenplum and Teradata are just getting too expensive. Particularly compared against its open source set, I think that's really the one key piece where Vertica might have a little bit more ladder room. It was always the leader in terms of pricing against Greenplum and Teradata, so that's why Vertica turned up again for us, but now that the open source solutions are trying to compete a little bit better in terms of stability, that's where we sometimes consider change. Which other solutions did I evaluate? I evaluated Teradata, and another, but I didn't like either of them, not for what we needed. What other advice do I have? The pros are, if you have columnar processing, then this is in your top three solutions. I think the con is the software pricing, and licensing needs to start getting more competitive with the open source solutions, or they need to market their stability a lot more. Test out the solution. Most people who test it buy it. So that's the biggest draw that it has, you can test in a day. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2018-01-28T00:00:00-05:00
Rated 5 out of 5 by from The engine analyses offline usage and sends customers alerts when they exceed certain limits. What is most valuable? * Quick retrieval of data * Fast upload of data How has it helped my organization? Vertica was a key component in a billing systems analytic engine. Among other functionalities, the engine is constantly analysing offline usage and sending customers alerts when they exceed certain limits. What needs improvement? It would be hugely beneficial if HP Vertica offered stored procedures. For how long have I used the solution? I have used it for five years. What was my experience with deployment of the solution? As a green field solution, the features of the application were not clear and the system integrator was not up to the mark. What do I think about the stability of the solution? We did not encounter hardly any stability issues. What do I think about the scalability of the solution? We did not encounter hardly any scalability issues. How is customer service and technical support? Customer Service: It was a green field solution, and getting quick customer service was a challenge. Technical Support: Technical support is scarce in Australia. Which solutions did we use previously? We did not previously use a different solution. How was the initial setup? Initial setup is straightforward. What about the implementation team? We implemented it through a vendor. The team was good, but they were not experts. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2017-04-05T00:00:00-04:00
Rated 5 out of 5 by from I like the Query Performance. Valuable Features: Query Performance. Room for Improvement: More analytical functions. Optimization around DML operations such that we be able to use it more. I understand that Vertica is not meant for that, but I would really love it if it has capability to support procedural processing. Optimization around DML refers to fast DELETE and UPDATE statement such that we can leverage Vertica around those operations. I do understand that Vertica is not meant as an OLTP system, neither I'm asking to have it similar but if DML operations can be optimized, that would be admirable. Regarding, my comment on the capability to support procedural processing - Vertica as of now is mainly used via SQL only. If we have to use any procedure based operation, we do it via User Defined Functions. If within Vertica itself, we have the capability to create & execute procedure similar to that for functions, it would be a plus. Again, I do understand that this may be against the architecture of Vertica but if there is anything that can be revised to get these supported, that would be preferred. Use of Solution: 3+ years Deployment Issues: Initially yes, but now we're used to it. Challenges do come up but it's all well understood. Stability Issues: We had confronted couple of issues during Vertica upgrades for which we do align with your support group. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-09-01T00:00:00-04:00
Rated 5 out of 5 by from Has improved the majority of our ETL operations, but performance degrades seriously for large datasets What is our primary use case? We use this solution as our data warehouse. It handles our analytics and we have power users connected. How has it helped my organization? Eighty percent of the ETL operations have improved since implementing this solution. Complex queries are challenging to improve. What is most valuable? This most valuable feature is the database designer, which helps significantly improve our storage footprint. What needs improvement? There is serious performance degradation for large datasets. Fact-to-fact joins on multi-billion record tables perform poorly. Star schema joins also perform poorly if the fact tables reach more than one billion records and the dimension tables reach more than one million records. For how long have I used the solution? Two years. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2019-07-10T00:00:00-04:00
Rated 5 out of 5 by from Superior performance in speed and resilience makes this a very good warehousing solution What is our primary use case? We are very happy to have a good warehouse solution that we can run on-premises. Hopefully, at some stage next year we will start testing it on the cloud so we can experience more of a hybrid solution. We would like to have Vertica as a duplicate in the cloud as a data lake. That is "probably" and not guaranteed. We could go with another cloud solution but Vertica has been a good solution for us so far and we hope the cloud product is as good. On-premises, Vertica would still be used as our data warehouse solution. That would keep us where we know that the cost for the hardware is relatively reasonable where we have customers running reports in a way that is good for us financially. The cost-per-query is very low on-premises because there is no cost-per-query. At the moment we have customers running many thousands of reports a day and having Vertica gives us real-time insight into our data. What is most valuable? I think the most valuable thing about the product is the speed and resilience. I would say the strong, well-featured SQL engine with many built-in features — including machine-learning — is also a strong point. Those would be the main features that stand out for me. There are other valuable assets having to do with Vertica. I find that sometimes reports on other systems may be quicker for one or two users, but their concurrency is not as good as Vertica. I would have to say Vertica returns the queries pretty much all the time reliably while other products can sometimes run for 10 minutes and still fail. What needs improvement? Every product has room for improvement and Vertica is no different in that way. I think the geospatial could be better functionally in delivering geographically defined results. I also think the ability to perhaps directly link to other databases rather than just data sources and files would be another one. To be honest, things that might be improved is one of those areas where I could list a lot of minor things, but they are probably not very important compared to the two that I would use immediately. If there is going to be a focus on improvement, it might as well be prioritized. For new functionality, I think the possibility of adding triggers or programmatic pieces of code might be helpful, depending on the data coming in. It is difficult to say if it would work or cause more issues than it solves. I mean, that would be handy if the right people were using it, but it can be so easy to tax the resources if a person puts a query on a multi-million-row table and there is something triggering code going off somewhere else. That could potentially be a problem. An advanced query is probably going to perform badly unless queries and code are kept simple. But it is a difficult question. I have written up a list of little things I want them to improve. I think they implemented the geospatial solution in a way I would not have done it if I designed it personally. For how long have I used the solution? The amount of time that we have been using the solution is a little difficult to judge. For two years we were building out the solution and preparing, so it was not really deployed. Let's say it has been in service for the past five-plus years. What do I think about the stability of the solution? Vertica is extremely stable. In all our years of heavy use, we had one crash. That was because we had not puppetized the database. Our OS and our version of Vertica were getting older and it turned out that was the main issue we had. One thing I probably do not like about Vertica is how part of the resourcing tool works. If you have Vertica in the cloud in Eon mode, then you can have different clusters to isolate different types of data usage. So, if it is a situation where you have many small, quick, concurrent queries, you could have one node for that. I have one for doing Kafka and batch-loading. You can have one for machine-learning as well. But when you are on-premises, up until recently, you had only shared resources. I am not a big fan of it. It is good, but I am not a big fan of it. What do I think about the scalability of the solution? It is scalable. You just add extra nodes. But like all data solutions and all databases, you have to always consider how the data is stored, and how the data is queried. We have Elasticsearch and lots of other databases and they will perform differently when used for different tasks. The queries may not work well on one database the same way as on another. Vertica is really quick, but we still experience users writing some query that results in a timeout after running for 45 minutes. That is ridiculous and should never happen. I can look at that query, make a few little twists and turns on the syntax and it comes back in a second or two. Likewise, you try and match your data to your report. So the answer is always yes when you talk about scalability. All databases are scalable, but you do not always want to be scalable where the lack of knowledge of the users can get in the way of the system's performance due to no fault of the database. Lack of knowledge about how to use the database is more likely to be where the problem is. If what they have is a true hybrid where we can see data across cloud and locally, what has mirrored, and how we keep our data sets separate, the cloud may be a type of scalability solution. A lot of that opportunity comes down to licensing with Vertica and if it turns out that the cloud is just as efficient for us. I have more thinking to do about the fact we have customers running many, many thousands of reports a day that do not currently cost us anything. We have got to think about that side of things and how licensing for the cloud will affect our costs. How are customer service and technical support? I have contacted the technical support team fairly frequently. Often sometimes just with a question that was easier to ask than to look for the answer. Sometimes when I sent a message we would get a reply that they planned on doing this — whatever it was — but had not implemented it yet. I find the support very good, but I find sometimes I end up having to escalate past the first point of contact. After a bit, I got to recognize which names and which people were better when they were on the case. When it is quite a serious situation, I could always contact our sales manager because it is in his interest to browbeat a few people to pay attention to customer issues. So support may not definitely be excellent, but it is certainly reasonably good as support probably always is. By comparison, Oracle does my head in as they are not good to deal with. Other support services I have encountered that are slightly better only seems to be better when they are smaller and newer teams. Which solution did I use previously and why did I switch? I have varied experience in this category of products and I have used a few different ones. We have an awful Oracle data warehouse, which is just not performing as it should. We have Vertica which provides us with a very good data warehouse solution, on the other hand. We are extremely happy with it. We did look at ParAccel, which is a component used with Amazon Redshift. We found that it worked on-premises, in the cloud, and I did extremely in-depth, rigorous testing on it, concurrency, size, volume, and it outperformed all the other databases. The cost was good as well. Some of our larger reports are running on 3.200 billion row tables and they are running in seconds. It might be something we use in the future. How was the initial setup? Actually, the setup of the product itself was straightforward and really quick. What did take some time was more of a case of developer time. Once I had the system installed, it stayed parked on the hardware because I had not set it up from a security standpoint. Once it was up and running, I was generating data, creating my first reports. I demonstrated how things that normally took us eight or nine hours on a Sunday and did not allow any real drill-down could be recreated in milliseconds with a lot more flexibility. It was more of a case that we had not had time to start building our dashboarding, communication with the customers, introductions to the new products, document the wonderful reports, and all that kind of stuff. I found it really straightforward to set up and run. I would say within two months of setting it up, I had all of my ingestion routines in place and everything was formalized. I had done structures regarding directories and how data should be handled. My documentation was complete. It ends up that it was one of the easiest database products I have ever had to set up. When I mean setup myself, it all happened within our company. We deployed without any external help except maybe a few tech support calls. There were other people involved. Some things I could just set up. Other things I handed off to a team because I would not have the time, the resources for data cleansing, et cetera. Working with some other people helped to expedite the project. What was our ROI? With something like Vertica, I really saw the opportunity for generating ROI. It has had a really excellent ROI. As I was encouraging people to start using it, moving them over to it — browbeating people almost — I took a lot more of a hands-on approach. Apart from the operational side of things, it was mostly me running the show. It is hard to calculate the exact ROI, but it was clearly returning just on performance alone. Which other solutions did I evaluat... Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2020-08-24T00:00:00-04:00
Rated 5 out of 5 by from Columnar storage makes 'hot data' available much faster than a traditional RDBMS solution. Valuable Features Columnar storage makes 'hot data' available much faster than a traditional RDBMS solution. Also, Vertica scales up quickly and maintains good performance. Improvements to My Organization Performance management of high-traffic sites - Vertica's ease of scaling has been invaluable for one of our main customers. Room for Improvement I'm concerned that HP Enterprise has sold their software business, and worry about future investment to enhance predictive/machine-learning capabilities. Use of Solution 3 years. Stability Issues Not really.... Vertica shines on stability. Scalability Issues No, scalability is also a strength of the solution. Customer Service and Technical Support 9 out of 10. HPE has some excellent engineers who are eager to help us make Vertica work well. Previous Solutions I've been a 'full stack' data expert for years, started on Oracle and SQL Server, moved to Hadoop, Mongo, etc, but Vertica was the right fit for large enterprises with high performance demands and ease of scalability. Initial Setup Initial setup is a bit clunky, like most complex, tunable products can be. Pricing, Setup Cost and Licensing Negotiate when their fiscal year is about to close :) Other Advice It's a solid product that keeps its promises. I do worry about HP Enterprise's sale of Vertica to Micro-Focus Rating: 8/10 - it works very well, but some customers worry about 'Vendor lock-in'. Disclaimer: My company has a business relationship with this vendor other than being a customer:We are a Certified Vertica/IDOL (HAVEN) Big Data partner with HP Enterprise.
Date published: 2016-10-30T00:00:00-04:00
Rated 5 out of 5 by from It works well. When we ran into issues, there seemed to be a lot of different opinions for how to resolve them. Valuable Features: We use Vertica as our primary data warehouse. It works well, relatively, most of the time. Room for Improvement: I just expect it to work and be serviceable. When we ran into issues, there seemed to be a lot of different opinions for how to resolve the issues and that was the feedback I gave to them. You talked to one tech, you talk to a different tech they had a much different approach. That was a big frustration point for us. The upgrade path and which way we should go. So at the end it created a lot of confusion for us, so I wouldn't upgrade it again lightly. We're going to remain on it for the next year, but we'll probably re-evaluate at that point if we want to continue with Vertica or something else. Stability Issues: It's been stable since November and before that, to be fair, it was stable for quite a while. Scalability Issues: The reason we like Hadoop and others is because they scale up, pricing doesn't scale up at the same level. Vertica is a license per terabyte product. They do give you discounts the more volume you get, but it adds up over time fast. We could scale at a lower cost with than other solutions. Scaling was a pain point. Getting recommendation on how to set it up ultimately to provide the best performance, how many notes, other things. We got different answers from them. Previous Solutions: We use MongoDB for some of our other internal production apps. It's a lot more involved and more complex than we like to go for a, just standard data warehouse, but we might look at Hadoop or similar for that. Initial Setup: There's a lot of complexities with the upgrade and costs of data failures. That was last year. It was kind of good that I forgot about those pain points. Other Advice: I would recommend that they highly evaluate all their options. If they're just going to run a small data warehouse, it's probably not a bad solution. If it's something they know is going to grow dramatically and unpredictably? I don't know. I would evaluate hard. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-06-29T00:00:00-04:00
Rated 5 out of 5 by from Auto-projections make it easy to tune performance What is our primary use case? The primary use of Vertica is as a data warehouse to perform aggregate and summary reports. How has it helped my organization? This solution has allowed us to reduce the creation of summarized tables, as the user can perform queries on the fly. It has provided for the faster retrieval of records. What is most valuable? The performance is very good and the aggregate records are fast. Vertica Auto-Projections reduce the knowledge required by the DBA for tuning performance. What needs improvement? When it is about to reach the maximum storage capacity, it becomes slow. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2020-03-05T00:00:00-05:00
Rated 5 out of 5 by from We use it for marketing analytics. Documentation could be improved. Valuable Features * Compression / speed with highly complex queries Improvements to My Organization We use it ( https://www.itcentralstation.com/products/hpe-vertica ) for analytics (marketing). Room for Improvement * Performance tuning * Not much by way of any documentation: The explain plans are very difficult to read / understand. I tried to diagnose some specific queries using the DBD Vertica utility, etc. For one example of using the explain plan, the query was complex with lots of joins and so on (the query took up about three A4 pages), but the explain plan I printed out took up in excess of 32 A4 pages. How on earth would you read that? No visual tools were available that I could find. * Very little if any training available in the UK: Our company wasn't able to find any on the topic. We found very little if any documentation (from the vendor) that was of much use. * Cloning / export was not well documented; poor examples. Use of Solution I have used it for three years. I worked with versions 4-7.x. Stability Issues I occasionally encountered stability issues (more so in earlier versions). Scalability Issues I have not encountered any scalability issues. Customer Service and Technical Support Technical support is excellent. Initial Setup Initially when I first started, the documentation, etc. available was scarce. However, this has improved substantially. I was used to OLTP and DWH solutions based on technology such as Oracle, so some of the concepts are quite different. Other Solutions Considered Before choosing this product, other options were considered, e.g., Kognitio ( https://www.itcentralstation.com/products/kognitio-wx2 ). Other Advice It’s still not mainstream (especially in the UK) and I would say to some extent still ‘improving’ at each release, but it is enterprise ready and a hugely cheaper option than some. We did some like-for-like comparisons between HP ( https://www.itcentralstation.com/vendors/hewlett-packard-enterprise ) Vertica and Oracle Exadata ( https://www.itcentralstation.com/products/oracle-exadata ) (work load / timings) and the two compared favourably, with Vertica being faster than Oracle ( https://www.itcentralstation.com/vendors/oracle ) in all but the biggest and most complex of queries. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-09-29T00:00:00-04:00
Rated 5 out of 5 by from Any novice user can tune vertical queries with minimal training What is our primary use case? We use the product for compressed data store, fast reporting, and self healing analytical data workloads. It also helps with big data ingestions, processing, and reporting. How has it helped my organization? Bulk loads, batch loads, and micro-batch loads have made it possible for our organization to process near real-time ingestions and faster analytics. What is most valuable? * The tool for performance tuning and recommendations * Any novice user can tune vertical queries with minimal training (or no training at all). What needs improvement? * It should provide a GUI interface for data management and tuning. * Monitoring tools need to be lightweight. They should not take up heavy resources of the main server. For how long have I used the solution? One to three years. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2018-06-13T00:00:00-04:00
Rated 5 out of 5 by from It is the foundation of our new Data Warehouse platform because of the scalability and query speed. Valuable Features Scalability, query speed. Improvements to My Organization It is the foundation of our new Data Warehouse platform. Room for Improvement Data velocity and manageability. Use of Solution The utilization/launching project has lasted for a bit more than a year now. Deployment Issues There have been some issues with deleting and updating data from tables. Stability Issues No Scalability Issues No Customer Service and Technical Support Customer Service: I have not been in contact with their customer service. Technical Support: I have not been in contact with their tech support. Previous Solutions We used Oracle ( https://www.itcentralstation.com/vendors/oracle ) but it did not scale well enough Initial Setup It was straightforward. Implementation Team I was not involved with the implementation. ROI Don't know. Pricing, Setup Cost and Licensing The pricing is very flexible Other Solutions Considered There was a proof of concept for a number of technologies but I wasn't involved in those. Other Advice It looks promising. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-09-01T00:00:00-04:00
Rated 5 out of 5 by from Columnar database supports our advanced analytics and ETL process How has it helped my organization? Before we used Vertica we used another columnar database which turned out to be very unstable and its performance was inconsistent. Vertica turned that around, to the point that it is now our go-to database. We became Vertica partners. What is most valuable? Vertica is a columnar database, this support our developments in analytics, advanced analytics, and our ETL process with large sets of data. What needs improvement? I believe the installation process could be streamlined. For how long have I used the solution? One to three years. What do I think about the stability of the solution? No stability issues. What do I think about the scalability of the solution? No scalability issues. How is customer service and technical support? They are very professional and responsive. Which solutions did we use previously? See "Improvements to organization," above. How was the initial setup? There are some considerations to be evaluated before you start the installation, but the installer does the respective checks so things will function properly. And there are a lot of options. What's my experience with pricing, setup cost, and licensing? The first TB is free and you can use all the Vertica features. After 1TB you have to pay for licensing. The product is worth it, but be aware of this condition, and plan. The compression ratio is explained in the documentation. Which other solutions did I evaluate? Infobright and MonetDB. What other advice do I have? The technical requirements for the product are really important. The design tool for vertica is the core of the database for performance. Never forget to use it to create projections to optimize the storage compression and response times. Better compression means the 1TB mark takes longer to be reached. Disclaimer: My company has a business relationship with this vendor other than being a customer:Partner.
Date published: 2018-01-25T00:00:00-05:00
Rated 5 out of 5 by from All joint operations were enhanced by creating identically segmented projections What is most valuable? * I found the columnar storage, which increases performance of sequential record access, to be the most valuable feature. * I also like the projection feature, which increases query performance. How has it helped my organization? * The workload on our ETL tools were reduced. * All joint operations were enhanced by creating identically segmented projections. What needs improvement? Limitations in group by projections is where I would like to see an improvement. What was my experience with deployment of the solution? We have not had any issues with deployment. What do I think about the stability of the solution? We have not had any issues with stability. What do I think about the scalability of the solution? We have been able to scale it for our needs. What other advice do I have? It is a good database that can be used for ad hoc queries as well as analytical queries. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2017-11-02T00:00:00-04:00
Rated 5 out of 5 by from Its projections and encoding are excellent tools for tuning large volumes What is our primary use case? We push both raw and modeled data into a Vertica cluster. It is used mainly for internal analysis and Tableau reports by data scientists and analysts. How has it helped my organization? It is tremendously scalability, with excellent performance. Vertica gives knowledgeable users and DBAs excellent tools for tuning. What is most valuable? * Its projections and encoding are excellent tools for tuning large volumes. * The product is simple and elegant. * It has excellent written documentation. I am able to answer any question by querying on Google. What needs improvement? You need to know what you are doing to get the most out of Vertica. If you do not utilize the tuning tools like projections, encoding, partitions, and statistics, then performance and scalability will suffer. It would be great if this were a managed service in AWS. For how long have I used the solution? Three to five years. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2018-06-13T00:00:00-04:00
Rated 5 out of 5 by from Our typical run time for a query is now measured in seconds not hours. What is most valuable? Two of them: * The core feature, meaning their highly efficient columnar file format and execution engine along with a great coverage of ANSI SQL, provides our analysts with a highly expressive and performing platform. * The extensibility and efficiency provided by their C++ SDK. How has it helped my organization? Before Vertica, we used a combination of sharded RDBMSs and Hive: the typical runtime for a query was in the hours. It's now in the seconds, with way more data than then (we're talking hundreds of terabytes). What needs improvement? Whatever's out, the core is not always as great as the engine, especially their first version. That's true, for example, for the Kafka or Hadoop integration. But they're getting better release after release. For how long have I used the solution? Four years. What do I think about the stability of the solution? Vertica's code, being designed to use the hardware at its maximum, is very sensitive to low level changes such as kernel bumps or GLibC upgrades. It's also important to do tests on the storage layer (RAID controller + disks). What do I think about the scalability of the solution? The default layout (all nodes running spread) introduces latencies in query planning when you reach about 60 nodes, in our experience. Switching to a large cluster (one control node per rack) would be advised, way before reaching the 128 nodes hard limit. How is customer service and technical support? It's really great. One of the best I had to deal with. They also assisted us during the development phase of the custom components we've designed. Which solutions did we use previously? Not really in the same area (MPP databases). However, we ran benchmarks back then against a bunch of competitors and Vertica was one of the fastest, while being relatively cheap and able to accommodate our hardware. How was the initial setup? The setup per se was pretty straightforward. However, it took us some time to design the most efficient loading pattern from Hadoop. What's my experience with pricing, setup cost, and licensing? Nothing to advise really; try it out first, it's free up to three nodes and 1TB, and then get in contact with their sales guys. Which other solutions did I evaluate? We did evaluate mostly SAP HANA and SQL Server PDW back in 2013, along with a bunch of OSS solutions. What other advice do I have? If you plan to use Vertica for different workloads (in term of IO patterns, query frequency, dataset structure) plan to split your clusters: the mother of all cluster patterns becomes quite difficult to manage at some point. We today have around 20 clusters for different usages. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2017-06-27T00:00:00-04:00
Rated 5 out of 5 by from I like the fast analytical functions and ability to extend functionality. Valuable Features Bulk loading data using copy Fast analytical functions Ability to extend functionality Improvements to My Organization Great reporting. Room for Improvement Faster deletes! Use of Solution 4 years Deployment Issues None Stability Issues Sometimes users write bad queries that has brought down the cluster. Need a way to better manage resources. Scalability Issues None Customer Service and Technical Support Customer Service: Great Technical Support: Great Previous Solutions No Implementation Team In house implementation. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-09-01T00:00:00-04:00
Rated 5 out of 5 by from I like the clustering aspect with the share-nothing mentality. I also value the ease of maintenance. Valuable Features The biggest, most valuable feature for us is the clustering aspect with a share-nothing mentality. Most clusters usually require their own shared storage, shared subnet, etc. and this becomes a pain and a nightmare to maintain. The second most valuable feature is that it's very easy to maintain. It's a breeze once you know how to handle it with your scenario in mind. Improvements to My Organization Loading raw data and leveraging column store to quickly aggregate the values as well as run a general analysis were the biggest improvements we found. Before, we had to scrub the data or reformat, load it, possibly scrub it some more, and then run the first set of analysis, and so on. With Vertica, we were able to combine some of these steps, such as loading gzip data directly into the table and leveraging R in Vertica to run all of the analysis. Room for Improvement Developer Tools - Vertica really needs some kind of IDE plugin for a system such as Eclipse or IntelliJ. Developing external functions in Vertica can kind of be like shooting in the dark sometimes. Also, an improved monitor or monitoring with alerting built-in that actually works would be a welcome addition. They truly need a Python or some script that can handle all of the low-level system changes for you and find out how the customer has heavily modified their nodes before the install. Some automation here would help a lot. The product overall is a great product, however management tools as well as monitoring tools are lacking. The product does, however, offer a lot of information in the form of system views and tables, but most of the data is hard to translate with out the help of their support team. Use of Solution I have used HP Vertica in multiple companies over the last four years. We currently have it running on a three-node Centos cluster and a six-node Centos cluster. Deployment Issues There have been no issues with the deployment. Stability Issues There have been no issues with the stability. Scalability Issues We have had no issues scaling it for our needs. Customer Service and Technical Support Like everything else HP has support for, the support is very poor. You normally have to threaten to leave, not buy support renewals, or call your sales rep to talk to anyone who knows anything about the product. The community normally knows more than support and most of my questions or issues were resolved by searching the old community boards while I wait for overseas support to ask me to send them the logs again for the 50th time. Previous Solutions I have previously tried SQL PDW, Mongo, Cassandra for alternatives. Even though all of those products are in different landscapes, the Vertica column store ended up being the best thing that was needed. Initial Setup It is straightforward if you read the documents and have mid to senior-level knowledge of Linux. Non-Linux admins will find the setup complex and cumbersome since most are Windows admin and they want point-and-click. Implementation Team We implemented through our in-house team. You need to read the docs, then read them again, and then make yourself a cheat sheet. Once you have done the setup for a two-node cluster, do some Research and Development before taking the time to do a large production cluster or buy the license. ROI ROI is great compared to the previous solution, SQL Server. Pricing, Setup Cost and Licensing TCO is much lower given the Linux OS and the fact that Vertica is licensed by data size and not node count. The best advice for licensing is to make sure you have a proper data retention policy in place and well-documented as well as some growth expectations before buying. Following this, it will make sure you don't over or under buy. Other Advice If you are not Linux savvy, find a person that is. Make a cheat sheet with the commands and/or steps for your environment. If you are in the cloud, make sure to understand the networking aspect is completely different in AWS from it will be in your local data center. Failure to plan is planning to fail with Vertica implementation, and try not to mess up the spread as it's a pain to fix. If you read the documents, you will see what I am talking about. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-04-14T00:00:00-04:00
Rated 5 out of 5 by from It is scalable and worth the expense if you need the production capability that it can support. What is most valuable? It has a very good design with high query performance. It provides the scale out capability by adding additional servers instead of scaling up the servers. How has it helped my organization? It has provided much better performance than SQL Server for big data analytics. What needs improvement? I would like to see integration with the latest Hadoop ecosystem. For how long have I used the solution? We have used this solution for three years. What do I think about the stability of the solution? It is usually very stable, but we occasionally see some nodes going down. What do I think about the scalability of the solution? There have not been any scalability issues. We are able to support trillions of data elements by adding more servers. How is customer service and technical support? The technical support is pretty good. I would give it a rating of 9/10. Which solutions did we use previously? We used to use MS SQL Server. It is good for data transactions, but it is not good for big data analytics. What's my experience with pricing, setup cost, and licensing? It is pretty expensive, but it is worth it if you need the production capability that it can support. Which other solutions did I evaluate? We evaluated SQL Server and Teradata. What other advice do I have? It is worth a try if you are looking to provide a high-performance, big data analytics database. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2017-02-14T00:00:00-05:00
Rated 5 out of 5 by from The fact that it is a columnar database is valuable. Columnar storage has its own benefit with a large amount of data. Valuable Features The fact that it is a columnar database is valuable. Columnar storage has its own benefit with a large amount of data. It's superior to most traditional relational DB when dealing with a large amount of data. We believe that Vertica is one of the best players in this realm. Improvements to My Organization Large-volume queries are executed in a relatively short amount of time, so that we could develop reports that consume data in Vertica. Room for Improvement Speed: It's already doing what it is supposed to do in terms of speed but still, as a user, I hope it gets even faster. Specific to our company, we do store the data both in AWS S3 and Vertica. For some batch jobs, we decided to create a Spark ( https://www.itcentralstation.com/products/apache-spark ) job rather than Vertica operations for speed and/or scalability concerns. Maybe this is just due to the computation efficiency between SQL operations vs. a programmatic approach. Even with some optimization (adding projections for merge joins and grouped by pipelined), it's still taking a longer time than a Spark job in some cases. Use of Solution I have personally used it for about 2.5 years. Stability Issues I have not recently encountered any stability issues; we have good health checks/monitoring around Vertica now. Scalability Issues I have not encountered any scalability issues; I think it's scalable. Customer Service and Technical Support N/A; don't have much experience on this. Previous Solutions We do have some pipelines accessing raw data directly and process it as a batch Spark job. Why? I guess it's because the type of operations we do can be done easily in code vs. SQL. Other Advice I would recommend using Vertica for those people/teams having large denormalized fact tables that need to be processed efficiently. I worked around optimizing the query performance dealing with projections, merge joins and groupby pipelines. It paid off at the end. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-10-18T00:00:00-04:00
Rated 5 out of 5 by from It delivers speed and performance in query response time. Complicated multi-table queries perform well. Valuable Features Speed and performance: Vertica ( https://www.itcentralstation.com/products/hpe-vertica ) stands top among its peers in the MPP world, delivering unparalleled speed and performance in query response time. Its distributed architecture and use of projection (materialized version of data) beats most of its competitors. Improvements to My Organization This product is used for in-database analytics for reports and queries that require very fast response times. Complicated multi-table queries perform very well, and the company has improved on business operations looking at hot data from various dimensions. Room for Improvement Projections take up a lot of space and hence, compression can be improved. Installation can be more intuitive via a simple, lightweight web client instead of the command line. Use of Solution I have used it for two years. Stability Issues While Vertica is otherwise stable, sometimes there are issues with restores to the last checkpoint. Scalability Issues I have not encountered any scalability issues. Customer Service and Technical Support Technical support is very good and knowledgeable. Previous Solutions I previously used Postgres ( https://www.itcentralstation.com/products/postgresql ); switched as performance suffered due to data growth. Initial Setup Initial setup was straightforward through the command line. Pricing, Setup Cost and Licensing Negotiate; with HDFS, storage is cheap. Vertica charges per terabyte of compressed data. But the underlying architecture materializes data in a different order and hence space utilization is always heavy, even for a single table; add to that the replication factor. Other Solutions Considered Before choosing this product, we evaluated Netezza ( https://www.itcentralstation.com/products/netezza ) and ParAccel ( https://www.itcentralstation.com/products/actian-paraccel ). Other Advice Make sure the data and table structures are compact. Vertica will create many versions of the same data as a projection and isolated tables will increase size, increasing licensing cost. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-10-18T00:00:00-04:00
Rated 5 out of 5 by from Fast inserts, queries way faster than in SQL Server. Valuable Features: Fast inserts, queries way faster than in SQL Server ( https://www.itcentralstation.com/products/sql-server ). Improvements to My Organization: Certain research which was unattainable beforehand, now is in reach. Room for Improvement: Some GUI Tools out of the box, better python integration. I would love to see some nice query engine, tooled specifically to Vertica extensions of SQL (with IntelliSense). We currently use TOAD, but it has a lot of bugs and does not provide full support of all Vertica features. For example with the "copy to" command it is buggy - extremely hard to debug. Other issues would be better query plan display and better management tools like command line admin tools. (MC would probably solve a bit here, I saw a demo on the conference). We have several avid Python users in the company, but this how maybe lower priority after I reviewed my conference materials and found that Vertica now has native Python driver. Use of Solution: 2 years. Deployment Issues: I was acting as my own DBA for a while, so a lot of hurdles before. But things are getting easier as more people in the company bought into the solution. I also got HP Training in house. (Thanks Herb!) Scalability Issues: We can scale a lot, wish it was a bit more affordable. Previous Solutions: It complements our SQL Server solution. Implementation Team: Own efforts. Cost and Licensing Advice: Switch to per node from per TB. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-09-01T00:00:00-04:00
Rated 5 out of 5 by from Its scalability has enabled Pythian's clients to manage data with agility and scale accordingly. What is our primary use case? It has performed well for the analytical and data warehousing performance. It has enabled scalability and has added value to the business. How has it helped my organization? Its analytics has enabled Pythian's clients to get the business insights as quick as they wanted. Its lower maintenance has also improved the ROI. What is most valuable? HPE Vertica is a unique solution as it handles a huge magnitude of data with matchless speed and simplicity. One feature, which has really benefited us, is the scalability offered by Vertica as it has enabled Pythian's clients to manage data with agility. What needs improvement? The documentation could be improved with more examples of commands and step-by-step scenarios. For how long have I used the solution? Three to five years. What do I think about the stability of the solution? There were no stability issues. What do I think about the scalability of the solution? There were no scalability issues. How is customer service and technical support? The technical support is good, although it could be improved in terms of the response time and skill-set. Which solutions did we use previously? NA How was the initial setup? The setup was pretty straightforward as it doesn't take much; if you plan your infrastructure right, then it is a breeze. What about the implementation team? NO What's my experience with pricing, setup cost, and licensing? Read the fine print carefully. What other advice do I have? First, analyze your business requirements and if the analytics, scalability, and lower maintenance are your requirements then go for HPE Vertica. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2017-06-25T00:00:00-04:00
Rated 5 out of 5 by from Lack of Stored Procedures, packages, triggers make things difficult for developers What is most valuable? Partition and join back to node are easy and simple for DBAs. DBAs don’t need to add a partition every month/quarter like with other DBs. What needs improvement? There are a lot of limitations within this product and it makes things extremely hard for developers. It lacks Stored Procedure, packages, and triggers like other RDBMs. For how long have I used the solution? One to three years. What do I think about the stability of the solution? Yes, we have encountered issues with Projections and performance. How is customer service and technical support? Very bad support, I would rate it two out of 10. Which solutions did we use previously? We use DB2, Oracle , MySQL, MSSQL. We switched to Vertica to explore it for future projects. How was the initial setup? Easy setup. Much easier than setting up Oracle RAC. What's my experience with pricing, setup cost, and licensing? Licensing is based on size of the database. Which other solutions did I evaluate? They did a good PoC and we were impressed with Vertica. However, when we implemented, it was nightmare with bad support. What other advice do I have? My advice regarding this product is a definite "no", due to bad support. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2018-01-18T00:00:00-05:00
Rated 5 out of 5 by from I liked the auto-distribution to all nodes for fault tolerance and query performance. Valuable Features The auto-distribution to all nodes for fault tolerance and query performance was pretty amazing. Improvements to My Organization Our data warehouse at the time was a multi-terabyte PostgreSQL cluster. It worked really well, but we wanted to increase the size to many TB's and our due to our query and loading patterns we found greater performance from Vertica's multi-node warehouse. Room for Improvement In the versions I worked with, if a majority of the nodes were being loaded under heavy, sustained rates the nodes would see some dramatic decreases in performance due to the data shuffling that needed to occur between all the nodes. To work around that we ended up doing most of the loading in one or two nodes and that helped significantly. The synchronizations problems occurred when loading about 10 billion events, at a rate of about 100k tuples/second/node across 5 nodes. One of the suggestions from Vertica engineering was to increase the number of nodes to offset how much data was being sync'd per node. Use of Solution Extensive use of Vertica 5 as a production datawarehouse, and a POC for a client. Deployment Issues In earlier versions Vertica, it could sometimes be a pain to install on multiple nodes. In the most recent versions most of that pain has been fixed. Stability in earlier versions was compromised at times when the majority of the nodes were under heavy write loads. Customer Service and Technical Support The service and support from Vertica was excellent. Every tech and sales rep I dealt with was very responsive, pleasant, and helped me solve any engineering issues we ran into in very short order. Previous Solutions I have used Greenplum and Postgres extensively. The latter is an excellent general-purpose database and is entirely suitable for most data needs, however Vertica works really well in cases where you are storing and querying a lot of data that can be compressed and stored in columnar format, and you need your data auto-balanced across many nodes. Initial Setup The installation procedure was reasonably straightforward, but earlier versions of Vertica were a bit more tricky due to libraries and dependencies. The docs were unclear in a few places during the installation, particularly with OS' that were not fully compatible with the required libraries. I expect those issues have been resolved in the newest version (8 at this time). Implementation Team Implementation was done in-house, with excellent support from the Vertica engineers. Other Advice My advice is to clearly define your expectations, and benchmark performance in real-world-like environments. If you expect to be executing 100 queries per second and loading 10 million tuples per minute, then test that, and test several times that so you collect measurements about where the system is liable to break down. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-10-30T00:00:00-04:00
Rated 5 out of 5 by from Allows us to take volumes and process them at a very high speed What is our primary use case? Primary use case is advanced analytics over huge amounts of data. Vertica provides high speed access to high volumes. How has it helped my organization? Previous to Vertica, some analysis could not be made because of the amount of data needed. Vertica allowed us to take those volumes and process them at a very high speed. What is most valuable? Vertica's most outstanding features are the compression rates achieved and the speed of access of high volume data. What needs improvement? * Support is an area where it could get better. * Promotion/marketing must be improved, even though it is a very useful product at very good price, it is not as "popular" as it should be. For how long have I used the solution? One to three years. What do I think about the stability of the solution? Just some issues with clustering, but they were not Vertica's issues. What do I think about the scalability of the solution? None. How are customer service and technical support? It could be improved. If you previously used a different solution, which one did you use and why did you switch? I used Hadoop as the first approach. However, Vertica provided the best of both worlds (huge amounts of data and speed of access for analytics). How was the initial setup? Once you got your cluster setup and nodes properly working, it is very simple to set up Vertica. What about the implementation team? We did the implementation ourselves. What was our ROI? Huge. We are doing analytics that previously we could not. Which other solutions did I evaluate? We evaluated Exasol, but it came out to be too expensive for the use case. What other advice do I have? Do a good volumetric analysis to manage the storage needed. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2018-03-11T00:00:00-05:00
Rated 5 out of 5 by from It's fast and built for complex analytics queries with a large amount of data. Valuable Features The speed of Vertica out of the box with the ability it has to perform complex analytics queries. In other databases, information will return in hours or even days while in Vertica it will be finished in minutes or even seconds. This is the best feature it has. Improvements to My Organization Vertica is in our core technology stack. We are serving reports and dashboard to clients from it. It's very important to us that it fulfills its function correctly and provides us with an advantage over our competitors. Room for Improvement The internal documentation. As a DBA, I really want to understand how its internals works. It needs to handle high concurrency short queries better as Vertica is not handling these well, and we have had to develop our own tool to help us with our dashboard. Use of Solution I've been using it for five years. Stability Issues The only thing is that it is very sensitive to network glitches and every time it happens, a node will leave the cluster and we need to re-connect it. Apart from this, the stability is very good. Scalability Issues It is very easy to scale Vertica as you need. Customer Service and Technical Support It used to be 10/10 but now it's 8/10. Maybe it's because they were bought by HP which is a big company and the transition is hard. Previous Solutions The last company I worked for shifted from Oracle to Vertica. For our BI queries it's a huge win. Vertica is much better than any other raw store as it is built exactly for complex analytic queries with a huge amount of data. Initial Setup The earlier version wasn't that good to deploy, but now it's pretty easy to install. If you follow the documentation, you will be OK. Implementation Team We implemented it in-house. Since it's different than a raw store database, you need to understand the architecture in order to get the most out of Vertica. This means that you will need to design you data model to suit the Vertica architecture otherwise you will get the same performance as the solution you're replacing, or worse. If your implementation is not complex you can just put it in and you will get out of the box improvements, but for complex ones you need to know how Vertica works and build the right design. Other Advice It's a great tool but to get the most out of it you will have to design your models to fit it. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-06-23T00:00:00-04:00
Rated 5 out of 5 by from Replication is the main feature for my use. Valuable Features Replication Improvements to My Organization Replication and Node recovery in 8.0. Room for Improvement vbr.py needs to be improve to support diff no of nodes source to target. Use of Solution 5 years Deployment Issues No Stability Issues Yes Scalability Issues No Customer Service and Technical Support Customer Service: 8 Technical Support: 8/10 Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-09-01T00:00:00-04:00
Rated 5 out of 5 by from The architecture means it can process/ingest data in parallel to reporting and analyzing because of in-memory Write-Optimized Storage alongside the analytics optimized Read-Optimized Storage. What is most valuable? Vertica’s analytic capabilities are its key strength. It can aggregate and analyze data at massive scale and neatly bring the calculation logic to the data with external procedures in C, Java and R. The Vertica architecture means it can process/ingest data in parallel to reporting and analyzing because of its in-memory Write-Optimized Storage sitting alongside the analytics optimized Read-Optimized Storage. Which brings us to projections and the DB designer which intelligently structures how data is actually stored on disk to improve the queries you actually run against it. So tables are a logical construct which are operated on as per other DBMS systems, but there’s a whole next level of intelligence in optimization for querying that puts Vertica in another league. How has it helped my organization? Our consultancy has introduced Vertica to a number of clients, from small scale ones who benefit from the free tier and per TB pricing model to have a powerful analytics cluster fairly cheaply to large investment banks who have been able to handle data at a scale that wouldn’t otherwise be possible. What needs improvement? We’ve built a data ingestion tool to sit alongside Vertica for easy data loading, and I would personally like to see extended developer tooling suited to Vertica – think published PowerDesigner SQL dialect support, IDE with IntelliSense, and stored procedures which we’ve also had to build a work-around module for. For how long have I used the solution? Personally, I've used it for three to four years (since v6), but a few others in Thorium Data Science have used it for longer. What was my experience with deployment of the solution? We've had no issues. You do need to invest a little time to understand how to set things up and optimize for your workload, but it’s all well documented and there are consultancy firms who will happily help with that. What do I think about the stability of the solution? We've had no issues with the stability. What do I think about the scalability of the solution? We've had no issues scaling it. How is customer service and technical support? It's very good. HP have some technically smart guys and are willing to give access to them when you start using Vertica. We’ve had some great support from their engineering team with things like telling us about upcoming features (snapshotting, in this case), which were spot on for a need a client of ours had. We were looking into engineering a solution ourselves and HP happened to have just what we needed coming down the pipeline in the next version. Which solutions did we use previously? We previously used Exadata, which is typically very expensive by comparison. This is because Oracle throw top end hardware at the problem as opposed to HP Vertica’s commodity hardware and smart software approach. How was the initial setup? It takes some time to come to grips with the various considerations. I’d suggest bringing in a consultant if you don’t have the time or inclination to do it yourself as it takes going through and install and configuration one or two times to really understand the implications of the different options. What other advice do I have? The implementation itself is excellent with fantastic features, speed and scalability. They lose a point only for the development experience which relies on third party tooling like squirrel, and not having SQL based stored procedures. Go for it! Try the pre-installed VM which HP offers to have a play with it and get a feel for it. It can certainly scale better than any other RDBMS and pushes the envelope of SQL analysis so you can query/analyze/report “BIG-DATA” without having to resort to the complications associated with Hadoop & unstructured data analysis. If your data is structured and large Vertica is what you need. Disclaimer: My company has a business relationship with this vendor other than being a customer:We are an HP Partner offering consultancy on Vertica (as well as Oracle, SQL Server and other DBs).
Date published: 2016-04-24T00:00:00-04:00
Rated 5 out of 5 by from For me the most valuable aspect is the speed of columnar data. Valuable Features Speed of columnar data. Room for Improvement Performance tuning; user community is needed. Use of Solution 1 year Stability Issues Node recovery is very inconsistent and impacts performance. Scalability Issues Concurrency Customer Service and Technical Support Customer Service: Terrible Technical Support: Terrible Previous Solutions SQL Server ( https://www.itcentralstation.com/products/sql-server ) and Oracle. Initial Setup Simple Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-09-01T00:00:00-04:00
Rated 5 out of 5 by from We're able to test more models and improve accuracy. Valuable Features Group by performance Analytic functions Improvements to My Organization We could run group by queries thousand of times faster, we are able to test more models and improve accuracy. Room for Improvement Debug custom functions in r. Use of Solution One year Deployment Issues None Stability Issues None Scalability Issues None Customer Service and Technical Support Customer Service: Great! Email response is quickly and also within reported issues are resolved. Technical Support: Ggreat, they really understand what they are talking about. Initial Setup Straightforward, very easy. Implementation Team In house Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-09-01T00:00:00-04:00
Rated 5 out of 5 by from Improved my organization's functionality and performance How has it helped my organization? It has improved my organization's functionality and performance. What is most valuable? You don't have any more dependency on the local store. In order to build the on-prem process for Vertica, you need to make a lot of changes and be picky about choosing your hardware for it. On Eon, you just put it on S3, so you're not paying a penny for the stores anymore. That's the good thing about Eon. What needs improvement? We are looking for a cheaper deployment for the solution. Although we did a lot of benchmarks, like Redshift. We tried Redshift, it didn't work. It didn't work out for us as well. For how long have I used the solution? I have been using Vertica since 2009. What do I think about the stability of the solution? When you're on-prem, you're always worried about losing your nodes. It was hard to restore especially when you have big data. What do I think about the scalability of the solution? Scalability has been amazing. We have seen a lot of improvement. We have developers and we have a production demo. We have hosted clusters for customers, we have deployed customer scope. I can scribe them by petabytes. I can scale them by the number of users. It depends on the customers. For one project we can have 15 to 20 consecutive users, but they deal with petabytes of storage. How are customer service and technical support? Their support is really bad. Maybe Micro Focus has changed but they were not good before. They weren't really responsive. We've never had good support. I would rate it a three out of ten. I met with them two months ago. They asked why we didn't renew our support. They wasted a lot of our money. We've had really bad experiences with Vertica. Which solution did I use previously and why did I switch? We previously used Oracle and we decided to go for big data. How was the initial setup? The initial setup was straightforward for me, it's not complex at all. You need to be at least a bit of a database administrator and really get certified on Vertica in order to use it. What other advice do I have? My advice to someone considering Vertica is to go for it. Nothing is missing. I would rate it a ten out of ten. The only issues are support and the price. Which deployment model are you using for this solution? Public Cloud Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2020-11-29T00:00:00-05:00
Rated 5 out of 5 by from ?Data Warehouse response times have decreased?. It doesn't support stored procedures in the way we are used to thinking of them. Valuable Features Speed in query in general and specifically in aggregate functions on multi-million rows tables. Improvements to My Organization Data Warehouse response times have decreased of one order of magnitude with respect to the previous solution (SQL Server + Oracle). Room for Improvement Sadly, it does not support stored procedures in the way we are used to thinking of them. There is the possibility to code plug-in in C++, but that's out of our reach. Correlated sub-queries are another point where we'd love to see enhancements, plus the overall choice of functions available. ETL with SSIS was not as easy as one we had expected (must remember to COMMIT and we had some issues with datetime + timezone, but that's was probably our fault). OleDB and .NET providers need some touches; and another great improvement would be support for Entity Framework, which so far I haven't seen. There is no serious graphical IDE for HPE Vertica, that's frustrating. One free option available is DbVisualizer for Vertica, but it's a bit basic. Use of Solution One year. Stability Issues We have a one node cluster on Red Hat and last week the DB went down. The setting to restart the database is not very intuitive and by default the DB does not restart alone. After a reboot, which may be good in some environments, but leaves you with an insecurity feeling. Scalability Issues Our DB isin in the tens of Gigs, we did not need to scale yet. Customer Service and Technical Support N/A, not used. Previous Solutions We had SQL Server, switched for money reasons and space. But we're not sure yet, SQL Server is way more stable and predictable. Initial Setup No, the documentation is scarce on non standard setups. We had to create a virtual machine locally, set it up and then upload it to AWS. Pricing, Setup Cost and Licensing We use the free community license, plenty of space for our environment. If I had unlimited budget I'd buy a preinstalled instance on EC2, much faster, but costly. Other Solutions Considered Netezza, but I didn't like it. For no particular reason, but the feeling was not right. Redshift - I was not impressed by the performance. Google Big Query - we tried it. Other Advice Do COMMIT, and enable/enforce constraints because by default they ARE NOT!!!! Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-10-30T00:00:00-04:00
Rated 5 out of 5 by from Simple setup and responsive support. Valuable Features Ability to get top performance for in-advance known aggregative SQL queries. Improvements to My Organization HP Vertica is an outstanding backend for Big Data-scale interactive dashboards/BI. Achieving top performance however requires a deep understanding of the product architecture and experience in fine tuning of Vertica. Room for Improvement I really would like to see Vertica able to use heterogeneous storage (RAM, SSD, HDD). Another issue I have seen is that the SQL optimizer fails to make optimizations that competing products are able to do. That’s something that should be improved as well. Use of Solution I've been using it for two years. Deployment Issues We have had no issues with deployment. Stability Issues They should provide HA with Vertica, the cluster must be put behind Load Balancers. Scalability Issues There have been no issues scaling it for our needs. Customer Service and Technical Support I have no complaints, the HP guys were very responsive. Initial Setup The initial Vertica setup was really simple. Implementation Team In-house. The vendor team had many persons working on our project and we got an impression that it is difficult for them to focus on our requirements. Other Solutions Considered I have evaluated numerous competing products. HP Vertica was chosen for the top performance of aggregative queries. Other Advice It is very easy to start using Vertica, however getting the maximum performance from it is a fine art. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-04-04T00:00:00-04:00
Rated 5 out of 5 by from It has helped us escalate, we need information almost real-time. Valuable Features Analytical features are amazing, the integration is wonderful. Improvements to My Organization It has helped us escalate, we need information almost real-time. Room for Improvement Documentation, there are functions that are not documented. UDF SDK, I'd like to see a step by step simulator example in a manual. The read-me code is good, however, an example would be great for starters. Use of Solution 3 years Deployment Issues Yes, cluster migration takes time. Stability Issues Yes, in data streaming ROS containers is a pain to work with. Scalability Issues Not yet. Customer Service and Technical Support Customer Service: It is good, they answer in good time. There are times that they really don't come with a proper answer. Technical Support: Decent. Previous Solutions Yes, regular relational databases. We switched for scalability reasons. Implementation Team In-house. Other Solutions Considered Yes, Netezza ( https://www.itcentralstation.com/products/netezza ). Other Advice I like the new things they are introducing. I want to see more with Python. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-09-04T00:00:00-04:00
Rated 5 out of 5 by from It's enabled us to develop our new reporting system which is used as a SaaS by our users. Greater query concurrency is needed. Valuable Features MPP Analytical functions HDFS Copy Resource management Improvements to My Organization It's enabled us to develop our new reporting system which is used as a SaaS by hundreds of users. We can also load massive amounts of data in seconds and query it with SLA for online dashboards. Room for Improvement * Active-Active clusters with online replication. * Greater query concurrency. * Better documentation/white papers as there arte lots of undocumented issues. Use of Solution I've used it for three to four years. Scalability Issues Rebalancing after adding nodes is an issue in terms of resources and especially locking of tables. It would be nice if this could be more transparent. Customer Service and Technical Support 8/10 Other Advice If your product has lots of concurrent queries this solution is not suitable for you, or you need to implement a cache layer. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-06-23T00:00:00-04:00
Rated 5 out of 5 by from Having projections as a parallel for indexes in a simple MySQL helped keep our data access fast and optimized. More insight into what the product is doing would help debugging. Valuable Features Having projections as a parallel for indexes in a simple MySQL helped keep our data access fast and optimized. Improvements to My Organization This product has enabled us to keep very large amounts of data at hand for fast querying. With enough hardware force behind it, we were able to use Vertica as our primary reporting database without having to aggregate data, thus enabling us to provide many reports without having duplicated data or large aggregation steps. Room for Improvement We would like to see better documentation and examples as well as further simplicity in creating clusters, adding nodes, etc. I understand the GUI is very simple but sometimes more insight into what the product is doing and where errors are occurring would help debugging. Use of Solution We have used HP Vertica for three years. Deployment Issues We have found multiple issues with deployment. Deployment was by far the hardest step in the process. We have very little knowledge of how to set up projects, how they affect query times, and how much additional storage they require. Stability Issues We have had no stability issues. Scalability Issues Scalability was a problem given we had to host the solution ourselves. It would be great to have a cloud-based solution around Vertica. Also, we found it difficult to modify and update our schema as we grew. Part of the problem may have been that when we first started using Vertica we were inexperienced. Customer Service and Technical Support We paid for technical support for one year but did not use it very much so we discontinued its use. Previous Solutions Choosing Vertica was the first time we used a data warehouse solution for handling the large amounts of data we were starting to gather. Since then, we have switched from an internally hosted Vertica to Spark managed externally. Initial Setup The initial setup was complex. Implementation Team We implemented it in-house. I would advise anyone to use a vendor unless you have an in-house expert. ROI I do not have an ROI. It is fair to say that we could not have provided our product to customers without Vertica. Pricing, Setup Cost and Licensing I found paying for the amount of storage we used simple. It was a surprise because we underestimated how much storage projections use and definitely did not purchase the correct license for the amount of data we estimated we would be handling. Other Advice The product is great to use, but there is a steep learning curve initially. Also, we found limited resources for basic operations such as setup and deployment. Most tutorials and documentation were regarding how to run queries and use external tools such as Pentaho, which we weren’t using. We just wanted good explanations of how to optimize using projections, etc. I think it can be a great product if used correctly and implemented by a team who is familiar with the product. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-04-24T00:00:00-04:00
Rated 5 out of 5 by from We could use it to offer Analytics As A Service to our customers. Valuable Features Manage big data fast and easy. Room for Improvement The time that the mediation process takes and historical information that I can store. Deployment Issues Yes, there is a functionality in Vertica "Broadcast" that high the process level of our Network Switch Core. I had a serious problem with this because I interrupted the network service in the company. We have to change "Point to point". Customer Service and Technical Support Customer Service: Excellent! Technical Support: Excellent! Other Solutions Considered Yes, Netezza ( https://www.itcentralstation.com/products/netezza ) and SAP HANA ( https://www.itcentralstation.com/products/sap-hana ). Other Advice I would like HP to help me to do more uses cases with Vertica. We are very interested in becoming a Business Partner in order to offer Analytics As A Service to our customers. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-09-01T00:00:00-04:00
Rated 5 out of 5 by from We can quickly identify with the root cause analysis where trends are. Valuable Features: We're just now getting into Vertica, but it allows us to store and access big data very quickly. It comes down to being able to quickly identify where the root cause analysis is and where trends are, so you can actually try to almost predict where problems are before they really become a problem. Improvements to My Organization: The ability to access in-store, big data, and be able to create keywords for faster resolution and look up an individual, hey we did this problem before. It'll show you all the steps and everything, along with different products. Vertica is pretty much the database behind it. It really does the performance aspect of it. Room for Improvement: I guess really the only thing there is if you get a server big enough to handle Vertica, it does just fine. If you're working in a small business, it will tend to overtake most of their budget from a cost perspective because you need so many servers, so much storage, to be able to handle all that stuff. Stability Issues: It's very stable. Initial Setup: We had no issues deploying it. Other Solutions Considered: I did not really look at any competition. Basically, it's like I said, we're an HP shop and a lot of their applications are going to a Vertica database for its storage and processing of data. We were doing a lot of Oracle, but Oracle was actually moving towards Vertica in our environment. Other Advice: Make sure you understand how much data that you're going to be incorporating into the big data, so you can actually define the amount of storage and redundant storage appropriately. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-07-06T00:00:00-04:00
Rated 5 out of 5 by from In a PoC, query performance outperformed other solutions. What is most valuable? We are evaluating storage and database ( https://www.itcentralstation.com/categories/data-warehouse ) solutions for an OLAP application with following requirements: * Extract, transform and load high velocity and volume of a numerical data stream on a distributed system. * Interactive (less than 20 sec latency) query performance for critical group-bys. Vertica ( https://www.itcentralstation.com/products/hpe-vertica ) is superior to other solutions in query performance. How has it helped my organization? We have not yet integrated the solution. What needs improvement? Vertica’s resource demands for RAM and I/O during load and storage were challenging for our platform. They recommend reserving 40% of storage for Vertica’s internal usage. Lower I/O usage during load is also highly desirable. For how long have I used the solution? The solution is not integrated into our product. We engaged in a PoC for 2-3 months in 2015 and put the evaluation on hold due to other project priorities. What do I think about the stability of the solution? We did not encounter any issues with stability. What do I think about the scalability of the solution? We did not encounter any issues with scalability. How is customer service and technical support? The level of technical support by the sales engineers during our PoC was excellent. How was the initial setup? Well-organized, online documentation made the initial setup fairly straightforward. What about the implementation team? Our in-house team worked on the PoC. Which other solutions did I evaluate? We evaluated a number of open-source and proprietary databases, as well as an in-house solution. Our PoC has been put on hold and we have not made final decision on a solution. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-11-23T00:00:00-05:00
Rated 5 out of 5 by from I like Recovery by table. I would like messages to Vertica startup commands improved. Valuable Features: Recovery by table Copy cluster Improvements to My Organization: VBR backup used to take more than one week to back up 70 TB of data. After upgrading to latest version, it is taking about 48 hours. Room for Improvement: Improve Vertica logging and messages to Vertica startup commands. Use of Solution: 4 years Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-09-01T00:00:00-04:00
Rated 5 out of 5 by from Its column-oriented architecture makes it a database specialized for data warehouses. What is most valuable? Vertica is an excellent data warehouse platform. Its column-oriented architecture makes it a powerful database specialized for data warehouses. Data should be designed around a star schema. Data is accessed via SQL, which most developers are already familiar with. Vertica is "catching on" in the software market, so its user knowledge base is gradually increasing. The price seems reasonable, the product is reliable, and it uses SQL, so developers don't need to learn a new language. How has it helped my organization? It provides very fast results for analysts running reports. These reports are crucial to help our clients strategize their targeted marketing. What needs improvement? Vertica is relatively new and needs some polish and refinement, but its core functionality is excellent. Documentation overall is fair to good; but lacks continuity or cohesiveness in places. Although its knowledge base is increasing, it is still relatively small, making some issues difficult to diagnose without consulting Vertica Tech Support. Vertica does not have native stored procedures or a native scripting language. Instead, external functions (which can be called from within Vertica) using Java, C++, Linux shell scripting, etc., are supported. This is an unpleasant surprise for many developers, but I feel this has not been a big hindrance in my experience. Complex business logic probably does not belong in a high-performance data warehouse platform. Rather, this should be taken care of during ETL. For how long have I used the solution? I have 3+ years of experience with Vertica. What was my experience with deployment of the solution? Deployment had only a few minor issues that one finds with most software. What do I think about the stability of the solution? It has been very stable. How is customer service and technical support? I would give technical support 8 out of 10. They have been responsive, professional and knowledgeable. Which solutions did we use previously? * I have used traditional, row-oriented relational databases like SQL Server, Oracle and PostgreSQL for data warehousing. They are optimized for handling transactions, not data warehousing. Vertica is optimized for data warehousing and that was very clearly demonstrated in its ability to scan large amounts of data at high speed. It is also very fast at loading data. * Vertica uses a distributed, shared-nothing architecture which allows for nodes to be added (or removed) according to need. This is a very scalable architecture which is very difficult to achieve with traditional row-oriented databases. * Compared to Hadoop, Hive, and Spark, Vertica is much more adept at handling concurrent users. How was the initial setup? Installation is recommended for someone familiar with Linux (the only OS available for Vertica). For developers with a Linux background, the issues are very manageable. Documentation is good for the installation, so follow it carefully, step-by-step. What about the implementation team? Implementation was in-house. No significant issues were encountered. What was our ROI? ROI is good because Vertica, while not cheap, is a better performer than traditional databases. What other advice do I have? * Understand that its strengths depend on a good data warehouse design using a star schema. It was never intended for high volumes of small, randomly distributed inserts, updates and deletes that are typically found in transactional databases. * It uses column-oriented architecture. It is important to study aspects of this architecture and to implement them and modify them as the database grows in size and more users access the system. This is especially true for projections, run-length encoding, sorting and column ordering. It is important to understand these aspects in order to truly maximize Vertica's performance. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2017-02-23T00:00:00-05:00
Rated 5 out of 5 by from We can process vast amounts of data, fast. Valuable Features Super-fast aggregated results from massive data. Improvements to My Organization We can process vast amounts of data, fast and with a high degree of reliability. Room for Improvement Better feedback from installation. I would like to see more meaningful errors returned and more graceful handling of those. Thankfully, we don't often hit error conditions. Use of Solution 4 years. Deployment Issues No Stability Issues No Scalability Issues Depends on the environment. Generally pretty good. If you have a large catalog, you can get timeouts adding nodes. Large catalog issues have been dealt with it recent releases so this should make scaling up even more robust. Customer Service and Technical Support Excellent. It can take some time to get to the right people but generally our issues are all addressed in an acceptable timeframe. Previous Solutions Greenplum ( https://www.itcentralstation.com/products/emc-greenplum ). It was less stable. Vertica is very robust and recovers predictably from unexpected infrastructure failures. Other Advice Great overall solution. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-09-01T00:00:00-04:00
Rated 5 out of 5 by from A SQL-based compute platform like Vertica enables far less human overhead in operations and analytics. Valuable Features: Scale-out, analytical functions, ML. Improvements to My Organization: We are an HP partner. A SQL-based compute platform like Vertica enables far less human overhead in operations and analytics. Room for Improvement: More ML, both data prep, models, evaluation and workflow. Improved support for deep analytics/ predictive modelling with machine learning algorithms. This area of analytics need a stack of functionality in order to support the scenario. The needed functionality includes: * Data preparation. Scaling, centering, removing skewness, gap filling, pivoting, feature selection and feature generation * Algorithms/models. Non-linear models in general. More specifically, penalized models, tree/rule-based models (incl. ensambles), SVM, MARS, Neural networks, K-nearest neighbours, Naïve bayes, etc. * Support the concept of a “data processing pipeline” with data prep. + model. One would typically use “a pipeline” as the overall logical unit used to produce predictions/scoring. * Automatic model evaluation/tuning. With algorithms requiring tuning, support for automated testing of different settings/tuning parameters is very useful. Should include (k fold) cross validation and bootstrap for model evaluation * Some sort of hooks to use external models in a pipeline i.e. data prep in Vertica + model from Spark/R. * Parity functionality for the Java SDK compared to C++. Today the C++ SDK is the most feature rich. The request is to bring (and keep) the Java SDK up to feature parity with C++. * Streaming data and notifications/alerts. Streaming data is starting to get well supported with the Kafka integration. Now we just need a hook to issue notifications on streaming data. That is, running some sort of evaluation on incoming records (as they arrive to the Vertica tables) and possibly raising a notification. Use of Solution: Two years. Deployment Issues: No, not really. Stability Issues: No. Scalability Issues: No. Previous Solutions: Postgresql, MySQL ( https://www.itcentralstation.com/products/mysql ), SQL Server ( https://www.itcentralstation.com/products/sql-server ). Switched because of scalability and reliability, analytics functionality. V being a better engineered product. Initial Setup: Straightforward. Good docs helped a lot. Cost and Licensing Advice: Its reasonably priced for non-trivial data problems. Other Solutions Considered: Yes, Hadoop / Spark, SQL Server. Other Advice: See additional functionality above. Disclaimer: My company has a business relationship with this vendor other than being a customer:We are a vendor partner.
Date published: 2016-09-01T00:00:00-04:00
Rated 5 out of 5 by from The most valuable feature for me is the columnar data store. Valuable Features: Columnar data store Room for Improvement: Add geospatial indexes (sounds like they have done it in version 8.0) Deployment Issues: No Stability Issues: No Scalability Issues: No Customer Service: Above average Initial Setup: Setup was very simple Disclaimer: My company has a business relationship with this vendor other than being a customer:We are partners with HPE
Date published: 2016-08-31T00:00:00-04:00
Rated 5 out of 5 by from The biggest performance improvements are for queries that have to analyze a large amount of historical data. Valuable Features: Fast query processing for historical data analytics. Write Optimized Store (WOS) continuous data loading without drastically impacting performance of OLAP queries. It's one of the few columnar databases that has the capability to provide near real time data delivery for analytics with minimal delay sourcing data from traditional databases or NoSQL data stores or any unstructured data sources. Improvements to My Organization: With traditional RDBMS historical data analysis or any complex queries took minutes to complete. With the addition of Vertica to handle big data queries, these reports are now returned in under 15 seconds. The biggest performance improvements obviously are for queries that have to analyze a large amount of historical data. Room for Improvement: Stability, scalability (3 node Community Edition) and backup/restore all need to be worked on. Without proper work load management and resource pool allocation, any batch/ETL or streaming jobs which refreshes data frequently will impair OLAP query performance. Use of Solution: We've been using the three node cluster for about one and a half years. Stability Issues: We had several incidents where SQL queries with UDF predicates would shutdown the cluster or sometimes a single node. We worked with HP support to get these things fixed with subsequent versions of Vertica. Scalability Issues: With the Community Edition we are restricted to three nodes. We have a lot of enterprise clients who stress our cluster to its limits. The only advice I would give to new adopters is that if you want superior performance and reliability you are better off going all-in with the enterprise edition and a large number of nodes; assuming you have a lot of clients who run queries concurrently. Initial Setup: Setup and administration are very easy. Vertica was designed to be operational with minimal Database Administrator effort. Other Solutions Considered: We evaluated various other solutions but we chose Vertica because its SQL implementation is very similar to PostgreSQL, and therefore it saved us lot of development time re-writing SQL queries. Vertica seems to be one of the few columnar database which can handle both ETL/Batch jobs and OLAP queries simultaneously. We stream data into Vertica from RDBMS frequently than what is typically recommended for Columnar databases. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-06-23T00:00:00-04:00
Rated 5 out of 5 by from The most valuable feature is the merge function, which is essentially the upsert function. We've had issues with query time taking longer than expected for our volume of data. Valuable Features The most valuable feature is the merge function, which is essentially the upsert function. It's become our ELT pattern. Previously, when we used the ETL tool to manage upserts, the load time was significantly longer. The merge function load time is pretty much flat relative to the volume of records processed. Improvements to My Organization HP Vertica has helped us democratize data, making it available to users across the organization. Room for Improvement We've had issues with query time taking longer than expected for our volume of data. However, this is due to not understanding the characteristics of the database and how to better tune its performance. Use of Solution We've been using HP Vertica for three years, but only in the last year have we really started to leverage it more. We're moving to a clustered environment to support the scale out of our data warehouse. We use it as the database for the our data warehouse. In it's current configuration, we use it as a single node, but we're moving to a clustered environment, which is what the vendor recommends. Deployment Issues We had no issues with the deployment. Stability Issues We've had no issues with the stability. Scalability Issues We've had no issues scaling it. Customer Service and Technical Support I'd rate technical support as low to average. The tech support provides the usual canned response. We've had to learn most of how to harness the tool on our own. Previous Solutions I haven't used anything similar. Initial Setup HP Vertica was in place when I joined the company, but it wasn't used as extensively as it is now. Implementation Team We implemented it in-house, I believe. Other Advice Loading into HP Vertica is straightforward, similar to other data warehouse appliance databases such as Netezza. However, tuning it for querying requires a lot more thought. It uses projections that are similar to indexes. Knowing how to properly use projections does take time. One thing to be mindful of with columnar databases is that the fewer the columns in your query, the faster the performance. The number of rows impacts query time less. My advice would be to try out the database connecting to your ETL tools and perform time studies on the load and query times. It's a good database. It works similar to Netezza from my experience but it is a lot cheaper. Pricing is based on the size of the database. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2016-04-21T00:00:00-04:00
Rated 5 out of 5 by from Enhanced capabilities, good customer service, large data scalability and stable What is our primary use case? The solution is a BI solution that includes machine learning. Our company is involved in the distribution of water and we use it to capturing data for several points and to discover where there might have been a loss of drinkable water. There is a problem with the water distribution because the company that I'm working for has an index of 32% of water loss during the process of the distribution. These losses can be from a different source. It can be from leakage, it can be an error or on the meter read which can have many issues, sometimes the problem occurs in different hours depending on the pressure of the water network. We need to use artificial intelligence to collect millions of the data points to detect where the problem might be coming from. What is most valuable? The solution has great capabilities. The tool that instructs the internal database forward is easy to use and is very powerful. What needs improvement? The product could be less expensive and could benefit from a better marketing strategy. In a future release, I would like to have one application to help create intelligent models. For how long have I used the solution? We have been testing and developing the solution for two years. What do I think about the stability of the solution? We did not have any technical problem with the solution. What do I think about the scalability of the solution? The solution has great scalability. We started with one terabyte of compressed data, this is a lot of data and we never had problems with the scalability. You can have hundreds of terabytes with the solution if you want, it all depends on your needs. How are customer service and technical support? The customer service is very good. They could improve on their expertise and knowledge of bigger projects and their support for them. Some of their information about collecting data I was not satisfied with their help. They could improve on customer service a bit. I rate the technical support an eight out of ten. Which solution did I use previously and why did I switch? We currently use IDOL as well as Vertica. How was the initial setup? The product is not easy to set up because you need a lot of training. It has less to do about the product itself, but the knowledge on how to use it. For example, the spreadsheet product Excel, If you don't know mathematics, you will have difficulty to make big Excel model and that's the same with the Vertica. It's just only a tool and depending on your capabilities to design what you need. What about the implementation team? We are the developers of a solution and it is a very sophisticated project. It's something that we spent two years to develop. We already tested it and we are only waiting for the customer to try it and then purchase it. It has taken some time to implement the solution to the way we wanted for our company. What's my experience with pricing, setup cost, and licensing? It's difficult today to compete with open-source solutions. In these areas, there is a lot of competition and the price of this solution is a bit pricy. Which other solutions did I evaluate? We use another product called IDOL and use them both together as our solution. Sometimes you use both or sometimes you use each one separately. The two products are machine learning products but with different uses. IDOL has a more developed application and is much bigger than in Vertica. What other advice do I have? This solution is used by several big companies such as Bank of America, Uber, and Facebook. Where you need a BI with intelligence. We use the solution because it is very good, you can make interconnections with anything to collect the data, any type of data. I have tried other products and they did not fit as well as this one did, I recommend Vertica. I rate Vertica a nine out of ten. Which deployment model are you using for this solution? On-premises Disclaimer: My company has a business relationship with this vendor other than being a customer:Partner
Date published: 2020-12-31T00:00:00-05:00
Rated 5 out of 5 by from A user-friendly tool that needs to improve its documentation part What is our primary use case? In my company, we use Vertica as it's a tool meant to serve as database performance software and to make some selections, including some usual activities on a database revolving around options like select, insert, update, delete, and a few more. What is most valuable? The best thing about Vertica is that it is a supportive database performance software. Generally, the tool is used for performance and KPIs. What needs improvement? In my opinion, nothing needs improvement in the solution as it is a great product. The documentation of Vertica is an area with shortcomings where improvements are required. Vertica needs to increase its sustainability in the future. For how long have I used the solution? I have been using Vertica for two years. I am a user of the product. What do I think about the stability of the solution? The stability offered by the product depends on various factors. Honestly, in my company, we encounter some problems with Vertica, though it is something that depends on the applications for which one uses it. I consider the stability of Vertica to be okay. What do I think about the scalability of the solution? Around 100 people in my company use Vertica. How was the initial setup? The product's initial setup phase is extremely simple. The solution is deployed on the cloud. What's my experience with pricing, setup cost, and licensing? Vertica is an expensive tool. Which other solutions did I evaluate? My company chose Vertica over other products since I think that all the other products we use are meant for the children in our college. I don't exactly know the reason why my company chose Vertica. What other advice do I have? I would describe Vertica as a user-friendly product. The documentation part of Vertica is almost the same as the one for MySQL, which we have in our company. The documentation part of Vertica is very friendly enough to use, but I can never say that the documentation area is better. I don't use ChatGPT to help me with my queries since I try to deal with my issues and queries on my own. I don't want anything improved in the solution as it provides us with everything we require in our IT environment. If I know how to run a query, then the results generated by Vertica turn out to be okay. The stability offered by Vertica is something that depends on the application and the memory of the product. If you work with Vertica in any of your projects, you will see that it works better for you with much more resources than others. You won't encounter problems with Vertica, especially if your company's architects are better at managing and creating interfaces. I recommend Vertica to those who plan to use it since it is easy to configure and use. I don't think you would encounter any problems with Vertica. The syntax in Vertica is easy to use and user-friendly, which you can find on Google. I rate the overall tool a seven out of ten. Disclaimer: I am a real user, and this review is based on my own experience and opinions.
Date published: 2023-11-16T00:00:00-05:00

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