Vertica Reviews

Query Performance.

More analytical functions. Optimization around DML operations such that we be able to use it more. I understand that Vertica is not meant for that, but I would really love it if it has capability to support procedural processing.

Optimization around DML refers to fast DELETE and UPDATE statement such that we can leverage Vertica around those operations. I do understand that Vertica is not meant as an OLTP system, neither I'm asking to have it similar but if DML operations can be optimized, that would be admirable.

Regarding, my comment on the capability to support procedural processing - Vertica as of now is mainly used via SQL only. If we have to use any procedure based operation, we do it via User Defined Functions. If within Vertica itself, we have the capability to create & execute procedure similar to that for functions, it would be a plus. Again, I do understand that this may be against the architecture of Vertica but if there is anything that can be revised to get these supported, that would be preferred.

3+ years

Initially yes, but now we're used to it. Challenges do come up but it's all well understood.

We had confronted couple of issues during Vertica upgrades for which we do align with your support group.

Speed of columnar data.

Performance tuning; user community is needed.

1 year

Node recovery is very inconsistent and impacts performance.

Concurrency

Terrible

Terrible

SQL Server and Oracle.

Simple

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

Ability to get top performance for in-advance known aggregative SQL queries.

HP Vertica is an outstanding backend for Big Data-scale interactive dashboards/BI. Achieving top performance however requires a deep understanding of the product architecture and experience in fine tuning of Vertica.

I really would like to see Vertica able to use heterogeneous storage (RAM, SSD, HDD). Another issue I have seen is that the SQL optimizer fails to make optimizations that competing products are able to do. That’s something that should be improved as well.

I've been using it for two years.

We have had no issues with deployment.

They should provide HA with Vertica, the cluster must be put behind Load Balancers.

There have been no issues scaling it for our needs.

I have no complaints, the HP guys were very responsive.

The initial Vertica setup was really simple.

In-house. The vendor team had many persons working on our project and we got an impression that it is difficult for them to focus on our requirements.

I have evaluated numerous competing products. HP Vertica was chosen for the top performance of aggregative queries.

It is very easy to start using Vertica, however getting the maximum performance from it is a fine art.

MPP

Analytical functions

HDFS Copy

Resource management

It's enabled us to develop our new reporting system which is used as a SaaS by hundreds of users. We can also load massive amounts of data in seconds and query it with SLA for online dashboards.

• Active-Active clusters with online replication.
• Greater query concurrency.
• Better documentation/white papers as there arte lots of undocumented issues.

I've used it for three to four years.

Rebalancing after adding nodes is an issue in terms of resources and especially locking of tables. It would be nice if this could be more transparent.

8/10

If your product has lots of concurrent queries this solution is not suitable for you, or you need to implement a cache layer.

We are evaluating storage and database solutions for an OLAP application with following requirements:

• Extract, transform and load high velocity and volume of a numerical data stream on a distributed system.
• Interactive (less than 20 sec latency) query performance for critical group-bys.

Vertica is superior to other solutions in query performance.

We have not yet integrated the solution.

Vertica’s resource demands for RAM and I/O during load and storage were challenging for our platform. They recommend reserving 40% of storage for Vertica’s internal usage. Lower I/O usage during load is also highly desirable.

The solution is not integrated into our product. We engaged in a PoC for 2-3 months in 2015 and put the evaluation on hold due to other project priorities.

We did not encounter any issues with stability.

We did not encounter any issues with scalability.

The level of technical support by the sales engineers during our PoC was excellent.

Well-organized, online documentation made the initial setup fairly straightforward.

Our in-house team worked on the PoC.

We evaluated a number of open-source and proprietary databases, as well as an in-house solution. Our PoC has been put on hold and we have not made final decision on a solution.