OpenText Analytics Database (Vertica) Reviews

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.

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.

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.

I've been using it for five years.

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.

It is very easy to scale Vertica as you need.

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.

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.

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.

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.

It's a great tool but to get the most out of it you will have to design your models to fit it.

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.

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.

Getting the Management Console up and running as expected was a bit of a challenge.

We've been using it for one and a half years.

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 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.

We've never had to contact them.

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 of the database was straightforward.

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 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.

We evaluated Netezza and Teradata alongside Vertica.

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.

Having projections as a parallel for indexes in a simple MySQL helped keep our data access fast and optimized.

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.

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.

We have used HP Vertica for three years.

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.

We have had no stability 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.

We paid for technical support for one year but did not use it very much so we discontinued its use.

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.

The initial setup was complex.

We implemented it in-house. I would advise anyone to use a vendor unless you have an in-house expert.

I do not have an ROI. It is fair to say that we could not have provided our product to customers without Vertica.

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.

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.

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.

HP Vertica has helped us democratize data, making it available to users across the organization.

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.

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.

We had no issues with the deployment.

We've had no issues with the stability.

We've had no issues scaling it.

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.

I haven't used anything similar.

HP Vertica was in place when I joined the company, but it wasn't used as extensively as it is now.

We implemented it in-house, I believe.

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.

Ability to get top performance for in-advance known aggregative SQL queries.

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.

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.

I've been using it for two years.

We have had no issues with deployment.

They should provide HA with Vertica, the cluster must be put behind Load Balancers.

There have been no issues scaling it for our needs.

I have no complaints, the HP guys were very responsive.

The initial Vertica setup was really simple.

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.

I have evaluated numerous competing products. HP Vertica was chosen for the top performance of aggregative queries.

It is very easy to start using Vertica, however getting the maximum performance from it is a fine art.

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.

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.

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.

We've been using it since January 2015.

We haven't had any issues with the deployment.

Stability is good, however the database crashed once because a query ran against a large XML data element.

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).

We haven’t needed tech support too much. So far so good.

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.

It seemed to be very straightforward. However, we had an experienced consult to do the setup.

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.

We have ran so little time in production that we don’t yet have a decent ROI or other calculations done.

The license model of HP Vertica is simple and transparent.

Just go for it and try it out; you can download the free Community edition from the HP Vertica website.