OpenText Analytics Database (Vertica) Reviews

User Defined Extensions

Analytic Functions

We were able to implement new algorithms without having to move data out of Vertica into a compute cluster. This allowed us to offer Analytics for Cybersecurity to our customers.

More Machine Learning algorithms--Random Forest for sure!

Very responsive

Excellent

In-house

Group by performance

Analytic functions

We could run group by queries thousand of times faster, we are able to test more models and improve accuracy.

Debug custom functions in r.

One year

None

None

None

Great! Email response is quickly and also within reported issues are resolved.

Ggreat, they really understand what they are talking about.

Straightforward, very easy.

In house

Recovery by table

Copy cluster

VBR backup used to take more than one week to back up 70 TB of data. After upgrading to latest version, it is taking about 48 hours.

Improve Vertica logging and messages to Vertica startup commands.

4 years

Columnar data store

Add geospatial indexes (sounds like they have done it in version 8.0)

No

No

No

Above average

Setup was very simple

• Massive data ingestion performance
• Performance
• SQL standard query engine

DWH core platform is based on it

• Machine learning implementations
• Support for Cloud based environments like Google Compute Engine

3 years

We're just now getting into Vertica, but it allows us to store and access big data very quickly. It comes down to being able to quickly identify where the root cause analysis is and where trends are, so you can actually try to almost predict where problems are before they really become a problem.

The ability to access in-store, big data, and be able to create keywords for faster resolution and look up an individual, hey we did this problem before. It'll show you all the steps and everything, along with different products. Vertica is pretty much the database behind it. It really does the performance aspect of it.

I guess really the only thing there is if you get a server big enough to handle Vertica, it does just fine. If you're working in a small business, it will tend to overtake most of their budget from a cost perspective because you need so many servers, so much storage, to be able to handle all that stuff.

It's very stable.

We had no issues deploying it.

I did not really look at any competition. Basically, it's like I said, we're an HP shop and a lot of their applications are going to a Vertica database for its storage and processing of data. We were doing a lot of Oracle, but Oracle was actually moving towards Vertica in our environment.

Make sure you understand how much data that you're going to be incorporating into the big data, so you can actually define the amount of storage and redundant storage appropriately.

We use Vertica as our primary data warehouse. It works well, relatively, most of the time.

I just expect it to work and be serviceable. When we ran into issues, there seemed to be a lot of different opinions for how to resolve the issues and that was the feedback I gave to them. You talked to one tech, you talk to a different tech they had a much different approach. That was a big frustration point for us.

The upgrade path and which way we should go. So at the end it created a lot of confusion for us, so I wouldn't upgrade it again lightly. We're going to remain on it for the next year, but we'll probably re-evaluate at that point if we want to continue with Vertica or something else.

It's been stable since November and before that, to be fair, it was stable for quite a while.

The reason we like Hadoop and others is because they scale up, pricing doesn't scale up at the same level. Vertica is a license per terabyte product. They do give you discounts the more volume you get, but it adds up over time fast. We could scale at a lower cost with than other solutions.

Scaling was a pain point. Getting recommendation on how to set it up ultimately to provide the best performance, how many notes, other things. We got different answers from them.

We use MongoDB for some of our other internal production apps. It's a lot more involved and more complex than we like to go for a, just standard data warehouse, but we might look at Hadoop or similar for that.

There's a lot of complexities with the upgrade and costs of data failures. That was last year. It was kind of good that I forgot about those pain points.

I would recommend that they highly evaluate all their options. If they're just going to run a small data warehouse, it's probably not a bad solution. If it's something they know is going to grow dramatically and unpredictably? I don't know. I would evaluate hard.

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.