Vertica Reviews

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

We use this solution as our data warehouse. It handles our analytics and we have power users connected.

Eighty percent of the ETL operations have improved since implementing this solution. Complex queries are challenging to improve.

This most valuable feature is the database designer, which helps significantly improve our storage footprint.

There is serious performance degradation for large datasets. Fact-to-fact joins on multi-billion record tables perform poorly. Star schema joins also perform poorly if the fact tables reach more than one billion records and the dimension tables reach more than one million records.

• Quick retrieval of data
• Fast upload of data

Vertica was a key component in a billing systems analytic engine. Among other functionalities, the engine is constantly analysing offline usage and sending customers alerts when they exceed certain limits.

It would be hugely beneficial if HP Vertica offered stored procedures.

I have used it for five years.

As a green field solution, the features of the application were not clear and the system integrator was not up to the mark.

We did not encounter hardly any stability issues.

We did not encounter hardly any scalability issues.

It was a green field solution, and getting quick customer service was a challenge.

Technical support is scarce in Australia.

We did not previously use a different solution.

Initial setup is straightforward.

We implemented it through a vendor. The team was good, but they were not experts.

It has a very good design with high query performance. It provides the scale out capability by adding additional servers instead of scaling up the servers.

It has provided much better performance than SQL Server for big data analytics.

I would like to see integration with the latest Hadoop ecosystem.

We have used this solution for three years.

It is usually very stable, but we occasionally see some nodes going down.

There have not been any scalability issues. We are able to support trillions of data elements by adding more servers.

The technical support is pretty good. I would give it a rating of 9/10.

We used to use MS SQL Server. It is good for data transactions, but it is not good for big data analytics.

It is pretty expensive, but it is worth it if you need the production capability that it can support.

We evaluated SQL Server and Teradata.

It is worth a try if you are looking to provide a high-performance, big data analytics database.

Replication

Replication and Node recovery in 8.0.

vbr.py needs to be improve to support diff no of nodes source to target.

5 years

No

Yes

No

8

8/10

Bulk loading data using copy

Fast analytical functions

Ability to extend functionality

Great reporting.

Faster deletes!

4 years

None

Sometimes users write bad queries that has brought down the cluster. Need a way to better manage resources.

None

Great

Great

No

In house implementation.

Manage big data fast and easy.

The time that the mediation process takes and historical information that I can store.

Yes, there is a functionality in Vertica "Broadcast" that high the process level of our Network Switch Core. I had a serious problem with this because I interrupted the network service in the company. We have to change "Point to point".

Excellent!

Excellent!

Yes, Netezza and SAP HANA.

I would like HP to help me to do more uses cases with Vertica. We are very interested in becoming a Business Partner in order to offer Analytics As A Service to our customers.

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