OpenText Analytics Database (Vertica) Reviews

• Massive data ingestion performance
• Performance
• SQL standard query engine

DWH core platform is based on it

• Machine learning implementations
• Support for Cloud based environments like Google Compute Engine

3 years

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.

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.

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.

It's very stable.

We had no issues deploying it.

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.

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.

We use Vertica as our primary data warehouse. It works well, relatively, most of the time.

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.

It's been stable since November and before that, to be fair, it was stable for quite a while.

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.

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.

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.

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.

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.

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

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.

I've been using Vertica for two and a half years.

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.

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.

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.

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.

My advice for pricing/licensing/ROI in a "proprietary proprietary“ comparison. You won’t achieve a better cost effectiveness with a different vendor.

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.

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.

• Speed
• Parallelization
• SQL language
• High Availability

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.

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.

I've been using it for five years. I started with version 4, which was prior to the HP acquisition.

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.

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 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.

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.

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.

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.

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.

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.

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.

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.

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.  

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.  

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.

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.

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:

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.

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.

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.  

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.

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).

We evaluated Vertica and Greenplum, and chose Vertica due to cost and a number of existing use cases that were nearly identical to ours.

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.

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.

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.

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.

We've been using the three node cluster for about one and a half years.

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.

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.

Setup and administration are very easy. Vertica was designed to be operational with minimal Database Administrator effort.

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.

MPP

Analytical functions

HDFS Copy

Resource management

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.

• Active-Active clusters with online replication.
• Greater query concurrency.
• Better documentation/white papers as there arte lots of undocumented issues.

I've used it for three to four years.

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.

8/10

If your product has lots of concurrent queries this solution is not suitable for you, or you need to implement a cache layer.