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.

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.

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.

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.

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.

We are resellers and we provide products for our customers.

Our clients are using this solution in two ways; one is for a data warehouse, and the second is for analytics in the database.

The data warehouse has exceedingly high performance and has the ability to do large scale queries very effectively. It fits well in large enterprises.

All features are valuable. It's a combination of capabilities that's all in one place, which is incredibly powerful.

For me, it's performance, scalability, low cost, and it's integrated into enterprise and big data environments.

Some of our small to medium-sized customers would like to see containerization and flexibility from the deployment standpoint. They don't currently offer this as a platform as a service. Snowflake is offering this capability.

They're available in the cloud. They're available on every cloud, but they're not available as a managed platform as a service offering.

We have been dealing with Vertica for two years. 

We use both version 9.3 and version 10. Version 10 is the latest one.

Vertica is a stable solution, it's rock solid. Production workloads being run on it are super steady. It's high availability, massively parallel processing. Nodes go down and you don't even notice.

This is a scalable solution. For example, if we look at Uber drivers, they are able to monitor the position and availability of the drivers and match that against the number of customers for every customer and every driver worldwide globally.

They do a geospatial analysis and calculate their search pricing. They are defined by geographical boundaries, they are defined by where the people are and where the drivers are. This is done for every city in the world for every driver. That gives you an idea of the scale they are able to do in this particular use case.

This gives you the idea of the scale, the performance, and the ability to do analytics in the database. They do this so much more cost-effectively than they would on any other platform.

Technical support is extremely good. They know the product and they're very good.
I don't have any complaints regarding technical support.

Vertica is known for its ease of administration. I would say that the initial setup is easier than most.

The price varies completely. Cost information is available publically where you can compare with other solutions.

From a cost perspective, the software is less than most of its competitors.

Customers save money by a smaller hardware footprint, fewer nodes, less storage, lower-cost storage, and no appliances. So it is typically a lot less money than an Oracle, Teradata, or Snowflake. 

Overall, they are highly competitive when it comes to pricing.

The customers love them. They absolutely love them.

Before implementing this solution, make sure that it is on the list and that you evaluate it.

I would rate Vertica a ten out of ten.

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.