Vertica Reviews

This solution is used as part of our data warehouse solution. We have some customer indexing content in this Vertica product. Vertica is a relational database that is used as part of our data warehouse implementation.

Vertica is a great product because customers can compress and code data. The infrastructure that data warehouse solutions need is a commodity server so that customers don't have to invest in infrastructure. Vertica is a column oriented database so the response of queries is very fast. 

In a future release, we would like to have artificial intelligence capabilities like neural networks. Customers are demanding this type of analytics.

We have been using this solution for six years. 

This is a stable solution.

This is a scalable solution. 

The customer service for this solution is good. 

Neutral

The initial setup is straightforward. 

It is important for those considering this solution to have some experience in database management solutions because Vertica is a relational database. Knowledge regarding SQL and any other database related skills is very important in order to implement or use this product correctly.

I would rate this solution a nine out of ten. 

The compute and processing engine returns the queries fast and let us use our analysis resources in a better utilization.

The concurrency got better in this version and we are able to run more queries and load concurrently.

We built an internal dashboard using the MicroStrategyto increase visibility to our management and our employees. Also, we built tool to expose the data to our selected partners and users to create better engagement with our platform.

• Loading times for “real time” sources - for example, loading from Spark creates a load on the DB at high scale
• Connectors to other sources such as Kafka or AWS Kinesis
• Better monitoring tools
• Better integration with cloud providers - we were missing some documentation regarding running Vertica on AWS

We've been using Vertica for a year.

In case of one HD failure in the cluster, the entire cluster got slower. We feel that it should be able to handle such issues.

No.

The support was slow and didn’t provide a solution in most cases. The community proved to be the better source for knowledge and problem solving.

Pretty straightforward, the installation was simple and we added more nodes easily as we grew.

Vertica is pretty expensive, take into account the servers and network costs before committing.

We evaluated both AWS Redshift and Google BigQuery.

Redshift didn’t fulfill our expectations regarding query latency at high scale (over 60 TB). Regarding BigQuery, we found the pricing structure pretty complex (payment per query and data processed) and harder to control.

Don't plan a production usage on high-scale straight on Vertica, use caching or other buffers between the users and the DB. Get yourself familiar with the DB architecture before planing your model (specifically, make sure you know ROS/WOS and projections). Try to avoid LAP before your schema gets stabilized.

Analytic functions.

We are trying to data mine customer event data. Having the ability invoke analytic functions without having write self join SQL statements ... just brilliant.

Ability to use analytic functions in where clauses, being able to use aliases in the where and order by clauses will make query writing/reading a lot easier.

2 years.

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

It has performed well for the analytical and data warehousing performance. It has enabled scalability and has added value to the business.

Its analytics has enabled Pythian's clients to get the business insights as quick as they wanted. Its lower maintenance has also improved the ROI.

HPE Vertica is a unique solution as it handles a huge magnitude of data with matchless speed and simplicity. One feature, which has really benefited us, is the scalability offered by Vertica as it has enabled Pythian's clients to manage data with agility.

The documentation could be improved with more examples of commands and step-by-step scenarios.

There were no stability issues.

There were no scalability issues.

The technical support is good, although it could be improved in terms of the response time and skill-set.

NA

The setup was pretty straightforward as it doesn't take much; if you plan your infrastructure right, then it is a breeze.

NO

Read the fine print carefully.

First, analyze your business requirements and if the analytics, scalability, and lower maintenance are your requirements then go for HPE Vertica.

• 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.

Columnar storage makes 'hot data' available much faster than a traditional RDBMS solution. Also, Vertica scales up quickly and maintains good performance.

Performance management of high-traffic sites - Vertica's ease of scaling has been invaluable for one of our main customers.

I'm concerned that HP Enterprise has sold their software business, and worry about future investment to enhance predictive/machine-learning capabilities.

3 years.

Not really.... Vertica shines on stability.

No, scalability is also a strength of the solution.

9 out of 10. HPE has some excellent engineers who are eager to help us make Vertica work well.

I've been a 'full stack' data expert for years, started on Oracle and SQL Server, moved to Hadoop, Mongo, etc, but Vertica was the right fit for large enterprises with high performance demands and ease of scalability.

Initial setup is a bit clunky, like most complex, tunable products can be.

Negotiate when their fiscal year is about to close :)

It's a solid product that keeps its promises. I do worry about HP Enterprise's sale of Vertica to Micro-Focus

Rating: 8/10 - it works very well, but some customers worry about 'Vendor lock-in'.

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.