OpenText Analytics Database (Vertica) Reviews

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.

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.

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.

We are using Vertica in our warehouse.

I have found that coding support could be simplified.

I have been using this solution for approximately five years.

The solution is stable.

I have found the solution to be scalable.

I have used the local support and I prefer them.

The price could be cheaper and it is best to negotiate the price.

I rate Vertica an eight out of ten.

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.

The solution has great capabilities. The tool that instructs the internal database forward is easy to use and is very powerful. 

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.

We have been testing and developing the solution for two years.

We did not have any technical problem with 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.

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.

We currently use IDOL as well as Vertica.

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. 

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.

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.

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. 

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.

It has improved my organization's functionality and performance. 

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. 

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.

I have been using Vertica since 2009.

When you're on-prem, you're always worried about losing your nodes. It was hard to restore especially when you have big data.

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.

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.

We previously used Oracle and we decided to go for big data. 

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. 

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.