Vertica Reviews

We use the solution in our data warehouse.

The solution is quick, has good compression data, and is not expensive.

Vertica is user-friendly.

The integration with AI has room for improvement. There is room for better machine learning.

I have been using the solution for 16 years.

The solution is stable.

The solution is easy to scale.

We have seven people using the solution.

The technical support is good.

The initial setup is straightforward. The deployment took four days.

The implementation was completed by a vendor.

The price is reasonable. The solution is free and we pay for the storage.

I give the solution a nine out of ten.

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.

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.

They could improve the integration and some of the features in the cloud version.

I have been using Vertica for approximately six years.

The solution is highly stable.

We have approximately 15 users using this solution in my organization.

Vertica is scalable.

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.

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.

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.

The pricing could improve, it is a little expensive.

I have evaluated Postgres.

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.

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.  

I am using Vertica for aggregations and dashboards.

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.

I have been using Vertica for three and a half years.

Over the last few months with the new release of Vertica, there have been stability problems. The performance should improve.

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.

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.

I have not used another similar solution to Vertica.

We had assistance from Vertica with the implementation of the solution.

I would advise others to try the solution out.

I rate Vertica a seven 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. 

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.

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.