OpenText Analytics Database (Vertica) Reviews

We are very happy to have a good warehouse solution that we can run on-premises. Next year we will start testing it on the cloud so we can progress to a hybrid solution. We would like to have Vertica in the cloud integrating with our data lake. 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 and flexible.  

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 large number of reports. At the moment we have customers running many thousands of reports a day and having Vertica gives us real-time insight into our data. The ROI with Vertica on premises has been sunstantial. 

Allow near realtime reports into vast amounts of data has given is insights into most areas of our business

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. 

When testing alternative columnar or in-memory databases the queries their speed may 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.  

Every product has room for improvement and Vertica is no different in that way. 

I think the geospatial is quick, but could be quicker.

Continue adding machine learning code to run directly on the database.  

I also think the ability to perhaps directly link to other databases rather than just data sources and files would be another one.  

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. 

W

Five-plus years in heavy use.  

Vertica is extremely stable. In all our years of heavy use, we had one crash at this was more likely OS related.  

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 cluster 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 which had to to be managed using resource pools.

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 several other database. They will perform differently when used for different tasks. The right database for the right task.

Vertica is really quick, but with poor query design a report can take far too long. 
Vertice EON mode allows for true user / query type scalability by firing up additional clusters as requirements change

I have contacted the technical support team fairly frequently. I find the support very good, but for more technical questions end up having to escalate past the first point of contact. 

I have varied experience in this category of products and I have used a few different ones. We have a legacy Oracle data warehouse, which is just not performing quick enough - hence the move to Vertica. Since moving to Vertica all the manual maintenance and speed issues of the Oracle data warehouse are left behind.

We did look at ParAccel, Vertica  and Kognitio when deciding we needed a fast database that could handle large volumes of data. Vertica 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 reasonable as well. Some of our larger reports are running on 3.200 billion row tables and they are running in seconds.

Actually, the setup of the product itself was straightforward and really quick. 

Once it was up and running and ingesting data we created our first customer facing reports very quickly. Replacing scheduled reports took us eight or nine hours on a Sunday and did not allow any real drill-down could be executed in milliseconds pm Vertica with a lot more flexibility. What takes time is building our dashboards, communication with the customers, introductions to the new products, document the reports.  

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 formalised. It ended up that it was one of the easiest database products I have ever had to set up.  

We deployed without any external help except maybe a few tech support calls.

With something like Vertica it has had a really excellent ROI. To allow realtime reporting opens up possibilities. Democratisation of data and having a front end reporting tool allows insights into data that would not have been possible.  

What differentiates Vertica from other competitors would probably be the ease of setup and ease of management. It can also ingest data from many sources, like Kafka, Parquet, and ORC (Apache Optimized Row Columnar). Vertica is quite flexible in how it handles its data. So mostly the flexibility and the ease of management separate it from most other products.  

Advice that I would give others who are considering this solution is what I always say for all products: you should heavily test your use cases and data with the product. There are different versions of software and there are always new software solutions. You always should do an exhaustive performance testing from the point of view of any database product. Better to let the product speak for itself. Test several vendor's products if possible. 

To be honest, it is hard to see too many issues with Vertica as a solution. I find a few weaknesses in it, but I think that is the same with all databases. I think when you are doing very large fact table to very large fact table joins pretty much every database will experience problems. Joining two tables that are many multi-million rows is just a large volume to process.  

Honestly, I think if you get a proof-of-concept up, you do your typical load and then keep multiplying concurrency and data volume — see how it works for concurrency, speed.  

Vertica so far has proven to be relatively hassle-free. But, like all databases, you do have to keep an eye on how people use it, particularly when it comes to reporting.  

On a scale from one to ten where one is the worst and ten is the best, I would rate Vertica as a nine.  

Primary use case is advanced analytics over huge amounts of data. Vertica provides high speed access to high volumes.

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.

Vertica's most outstanding features are the compression rates achieved and the speed of access of high volume data.

• 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.

One to three years.

Just some issues with clustering, but they were not Vertica's issues.

None.

It could be improved.

Positive

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).

Once you got your cluster setup and nodes properly working, it is very simple to set up Vertica.

We did the implementation ourselves.

Huge. We are doing analytics that previously we could not.

We evaluated Exasol, but it came out to be too expensive for the use case.

Do a good volumetric analysis to manage the storage needed.

The primary use case is machine learning and currently, I am working on IOT projects.

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. 

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.

The biggest problem is the cost of cloud deployment.

I have worked with Vertica for the past five years.

The initial setup is straightforward and easy deployment.

I would rate Vertica an eight out of ten.

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.

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. 

In a future release, we would like to have artificial intelligence capabilities like neural networks. Customers are demanding this type of analytics.

We have been using this solution for six years. 

This is a stable solution.

This is a scalable solution. 

The customer service for this solution is good. 

Neutral

The initial setup is straightforward. 

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. 

Our primary use case for this solution is data analytics.

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.

The integration of this solution with ODI could be improved. 

I have used this solution for 1 year.

This is a stable solution with a fast compression system.

This is a scalable solution. 

The technical support for this solution is really good. The support team are friendly and provide assistance quickly. 

Positive

The initial setup is straightforward. 

The pricing for this solution is very reasonable compared to other vendors.

I would rate this solution a ten out of ten. 

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.

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.

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.

I have been using this solution for four years.

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.

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.

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.

I use Vertica for traditional data warehouse reporting and some advanced analytics as well as real-time data processing or real-time analytics. I sell Vertica, so my clients' use cases vary. There are several types of users, and each company is going to have different requirements. And the number of users is not necessarily a great measure of usage if you're doing clickstream-type data on a website with massive numbers of queries coming in very quickly. But in other cases, you have people hammering it for reporting and various kinds of business use cases.

Vertica has a few features that I like. From an architecture standpoint, they have separated compute and storage. So you have low-cost object storage for primary storage and the ability to have several sub-clusters working off the same ObjectStore. So it provides workload isolation. Vertica handles analytics and large queries extremely well — very high performance —and on top of all of these features, Vertica has a very low total cost ownership.

Vertica offers a platform-as-a-service version, but their software-as-a-service solution is only available on AWS. They need to get a SaaS version on Azure and GCP as fast as possible. I know that's in their roadmap, but I can't wait.

I've been using Vertica for almost three years.

Vertica is rock-solid.

Vertica is massively scalable. My customers' workloads vary. While the number of users is not necessarily the ideal performance measure, the user bases range from a few dozen in smaller setups to thousands in the largest setups. And some of my customers have several hundred users on the platform concurrently.

I deal directly with Vertica's engineers, so I don't have much experience with their frontline tech support. However, the more senior tech support on the backline is just world-class. These guys are amazing. And they are exceedingly committed to their customers. I've seen them do crazy stuff to support a customer.

Setting up Vertica is pretty straightforward. There's nothing super fancy about deploying Vertica. Depending on what you're doing, deployment can take anywhere from 10 to 15 minutes to several hours. It's quick if you want to use the automatic tools, which work very well. And if you want to do your own thing or do it on-prem, then it's going to take you a little bit longer. And you don't need large teams to administer it afterward.

I rate Vertica 10 out of 10. Anyone thinking about using Vertica should try to understand more than its basic functionality. They should look at its more powerful features like advanced, predictive, and real-time analytics. And just to add, that in the world of data warehousing, it's more accurate to say "near real-time" rather than "real-time" analytics. 

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.

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.

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.

I have been using Vertica for about five years.

It's a stable solution.

Vertica is a scalable solution.

Technical support is good, and they react quickly.

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.

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.

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.