OpenText Analytics Database (Vertica) Reviews

We use the solution for the warehouse. We implement machine-learning solutions such as clustering or classification models.

We can implement advanced solutions with very interesting capabilities to review whether the customer returns the tool and the licensing cost.

Vertica uses advanced Azure technologies to compress raw data using indexing, allowing a large amount of data to be stored with minimal physical space. Advanced algorithms are employed in data compression.

Pricing could be more competitive.

I have been using Vertica for three years. We are using the V23 of the solution.

I rate the solution’s stability an eight out of ten.

100-200 users are using this solution.

I rate the solution’s scalability a nine out of ten.

Support is good.

The initial setup is straightforward. The deployment process includes creating a solar package to deploy this package on-premise or in a cloud environment. The solar package has all the configurations and components we need to implement as part of customer solutions. There are various software components requiring a specific configuration. So, we package this solar component and deploy it in the customer environment.

I rate the initial setup an eight out of ten, where one is difficult and ten is easy.

I rate the product’s pricing a seven out of ten, where one is cheap and ten is expensive.

You can implement a cluster of servers, and we should guarantee high availability in a disaster recovery scenario. You can use Vertica in a production environment with distributed workflows and workloads. Vertica is available and has parallel processing and other capabilities.

You can implement a cluster of servers to guarantee high availability and massive parallel processing. It's a very sophisticated solution.

Vertica can be used to implement machine learning models such as classification, clustering, and aggregation models to support various use cases depending on customer needs. We have already implemented some machine learning models to detect anomalies. Some employees have distinct patterns in their working behaviors. 

It is another feature-intelligent solution from OpenTex. It can implement or process structural data such as images, videos, text documents, and semi-structured data.

I recommend using this kind of solution because you can index your data and use a balancing algorithm to manage and retrieve data efficiently. Customers don't need a very large infrastructure to implement this type of solution. You can use it to implement advanced machine learning models, classification, and clustering. It also supports advanced artificial intelligence solutions.

Overall, I rate the solution a nine out of ten.

In this particular use case, our company is in the media industry and we rely exclusively on Vertica for our analytical and operational reporting requirements.

What I find personally beneficial about Vertica is its ability to scale effortlessly, regardless of the data load. 

In addition, there are several optimization techniques available to fine-tune queries, resulting in faster report generation times compared to any other databases I have worked with.

I appreciate the flexibility offered by Vertica's projections. It allows for modifying the primary projection without altering the tables, which helps to optimize queries without the need to modify the underlying data. 

This feature enables us to fine-tune our queries by modifying different projections, which is highly beneficial.

In my opinion, Vertica's documentation could be improved. Currently, there is not enough documentation available to gain a comprehensive understanding of the platform. Additionally, the community support for Vertica is limited, making it difficult to find assistance or resources when needed.

When it comes to data sharing or desktop usage, Snowflake has an advantage over Vertica and other platforms such as cash. Snowflake provides reporting capabilities to share data between two different accounts, which is not currently available in Vertica. This feature is particularly helpful when sharing data with third-party vendors or clients. However, Vertica does not provide such capabilities, and it is not possible to set up data sharing between two different accounts with just a few clicks, as it is possible in Snowflake.

Vertica is a solution that my team manages.

We have been working with Vertica for a year and a half.

We are currently using version nine, specifically 9.3 or a similar version. We have not yet upgraded to the latest version.

Vertica is always stable.

We have not had any stability issues with Vertica.

Vertica is a scalable solution.

I would rate the scalability an eight or nine out of ten based on the use case that we do.

We are a team that handles operational reporting, and our Vertica implementation is used by thousands of people. However, the team responsible for managing and writing code for Vertica consists of only around ten to twelve people.

I personally have not contacted technical support.

Snowflake is a platform that we use in our company. We have been using this solution for the last six months.

As a user of the platform, I don't engage in Snowflake development directly.

Instead, I use Snowflake as a platform where tables are already set up for me to work with. 

I do not handle any aspects of Snowflake management, such as table creation or sharing configurations, as these are typically set up with minimal clicks. 

My work revolves solely around Vertica, and I am responsible for handling everything related to Vertica.

Regarding the initial setup, I don't have direct involvement in it and cannot provide much comment. It's something that my team handles, and while they found it easy to set up, I don't have many specific insights to share.

Our team handled the deployment, we did it ourselves.

It is not difficult to maintain. 

We have a Database Performance Analyzer (DPA), and we've gained experience over time. I've been handling it for three years now.

I am aware that we have licensed it, but I have no knowledge of its cost. As I am not involved in that area.

We work with both Snowflake and Vertica solutions.

I am exploring the use of both Snowflake and Vertica for various use cases, and I am now evaluating which one would be the best fit for a new use case based on our requirements.

I would recommend using the Database Designer tool to design projections before actively using Vertica, instead of rushing into it like with other databases. Vertica is designed for different use cases, and designing projections beforehand can make things much easier later on. Vertica offers features that we believe people should take advantage of before going into production.

I would rate Vertica an eight out of ten.

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 hold financed data on the Vertica database, and clients use the data for reporting and other purposes.

Vertica provides benefits to our customers and helps with their performance.

The most valuable feature is Vertica's performance and the ease of using the database. Also, it is great for partnering with data.

We faced some challenges when trying to use the temporary tables feature. First, we installed Vertica on the AWS cloud and tried to read the data from Bitbucket to Vertica. We were able to read the data, but when we were trying to transform the data and load it into Vertica physical tables, we experienced performance issues.

Regarding additional features, we are unsure if Vertica has updated its features, but we've experienced difficulty in integrating with third-party tools. Clients use multiple technologies and value that integration. Sharing data with third parties should also be improved.

We have been using this solution for two years and are using the latest version.

It is a stable solution.

It is a scalable solution. Initially, we had issues with the scalability, but with the new version, Vertica resolved the issues.

Regarding how many users are using this solution, I do not have a specific number, but our organization is large. So, for example, in a unit with about fifteen clients, two to three clients use Vertica.

I rate this solution a seven out of ten.

Snowflake claims to have many more features than Vertica, but we cannot compare both solutions as we have not used Snowflake. However, if Vertica integrates the use of third-party tools, it would be great and more competitive.

We are using Vertica for dashboards, storing, retrieving, and processing data.

The most valuable feature of Vertica is the unmatchable database performance at a fraction of cost compared to other similar databases.

Vertica can improve automation and documentation.

I have been using Vertica for approximately seven years.

Vertica is stable. They have made improvements in this area but can still improve.

The scalability of Vertica is good.

We have approximately 100 users using this solution.

The support from Vertica is good, they are knowledgeable. However, sometimes there are some challenges when escalating our issue.

I have previously used Teradata long time ago. The price of Teradata was very high and hardware is vendor specific. Vertica can operate on comodity hardware and therefore easily scalable.

The initial setup of Vertica is straightforward.

The price of Vertica is less expensive than some competitors, such as Teradata.

We require one person for maintenance for the 100 users we have.

I rate Vertica an eight out of ten.

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.

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.