VMware Tanzu Greenplum Reviews

External tables to load the data from flat files.

It helped us in loading millions of data in quick time & improved query response.

More stability in terms of query result.

Five years - DCA V2.0 EMC & Greenplum Database

No.

Not usually, but sometimes we do.

No issues encountered.

Excellent.

Excellent.

We applied MPP Appliance for the first time earlier we were running on SMP’s.

It was straightforward.

Vendor- they had good expertise.

Good.

We also looked at Teradata.

Very good and cost effective with very good customer support.

• Distributed data for performance
• File loaders to reduce dependency on Informatica

Batch processing times have dramatically decreased from over 12 hours to under three hours. Much of this is converting off of Informatica and using distributed processing. Reporting performance also improved greatly.

Since we are upgrading to a new version at this time, it’s hard to say. But we seem to be replacing a disk on the appliance every week.

I've used it for six years.

There's no issues, although we are currently in the middle of an upgrade to v4.3.5.

It seems like we are replacing a disk on the appliance every week. Not a noticeable issue for users and batch processing is not adversely impacted.

Very good. Response times are good for service calls.

I believe the set-up was straightforward. I don’t remember any issues.

We used a vendor team. My advice is that the planning is critical. When converting processing jobs, convert them to PostgreSQL for better performance. Yes they could work as written previously, but you benefit using the features of the product immediately if you adjust the processing to match appliance. Use the bulk processing to your advantage.

We evaluated other solutions. Not sure of the reasons why this product was chosen.

It’s a good product. We moved from Oracle and I don’t want to go back.

The Greenplum loaders – their methods, insert, update and merge – were most valuable. The external table feature within Greenplum was also very valuable in achieving performance and scalability

A lot of customers use Greenplum and for their ETL use cases they use Informatica PWX for Greenplum, which helps them achieve transfer of data from a number of data sources into Greenplum. We can help customers to load data effortlessly and quickly.

It would be best if Greenplum would support array writes through ODBC drivers . Currently through Data Direct Greenplum drivers we can have single row inserts into Greenplum only. It would help if array loading is supported.

I have been using Greenplum loaders to load data into GreenPlum for three years.

There were no issues in deploying it.

The external table feature helps to make this a stable solution.

It scales to our and our customers needs as required.

The ongoing response from their support on certain technical issues has been slow. It would help if we can have a faster turn-around here.

There was no other solution used previously.

The installation and configuration is straightforward.

We implemented through a in-house team . The overall solution will be useful and is not complex

If the use case is going to be requiring a huge data transfer and big data analytics. This is a good product to use.

The primary use of this solution is for horizontal scalability.

We have an on-premises deployment.

The most valuable feature for us is horizontal scaling.

The deployment process for this solution could be made easier.

I saw some limitation with respect to the column store, and removing this would be an improvement.

This solution is stable enough. 

We are not yet sure about scalability, but we will see in the future.

We have not been in touch with technical support for this solution.

We were using MySQL prior to this solution.

The initial setup of this solution was not simple, but it was not too complex, either. I would say that it was of medium complexity.

Our deployment took approximately two days, although this was only a partial deployment. We have yet to add another node.

We performed the deployment in-house.

We are using the open-source version of this solution.

Prior to choosing this solution, we evaluated MySQL and PostgreSQL.

I would rate this solution a seven out of ten.

It is a very good appliance for data warehouse (DWH) usage.

• Very fast for query processing
• Parallel load
• Polymorphic storage

Before we had Oracle Exadata, some queries would take more than 20 hours of execution. With Greenplum, it take a few minutes.

It will be very useful if we could communicate with other database types from Greenplum (using a database link).

Four years.

No issues.

No issues.

Good. I would give their technical support a seven out of 10.

Yes, Oracle Exadata. Performance was the main criteria for switching to Greenplum.

It was a simple setup.

It is the best product with best fit for price/performance customer objectives.

We evaluated Oracle technology that we used before.

I encourage other customer to try Greenplum, specifically for DWH use. It is a very useful product.

MPP (Massive Parallel Processing); processing large amount of data.

We process billions of rows of data every hour; MPP architecture is important to process data in such volume.

• Better integration with big data tech stack
• Scalability: for example, system schema (pg_catalog) is one bottleneck for scalability

I've used it for four to five years.

The system has some bottleneck, like system schema; some commands (batch loading) is bottlenecked by master DB architecture

It's very poor.

It's very poor.

Used Greenplum originally. We have evaluated other products; the final decision is based on ROI

Products was installed by vendor; all ETL scripts and schema are designed and implemented in-house.

The product was installed by vendor; all ETL scripts and schema are designed and implemented in-house.

Greenplum has an open source version now.

Scalability is one major concern; once data reach certain level; the performance is dropped and much more issues will be triggered, like disk error; out of memory; etc. Be sure that you proper scope your need (including growth) before the decision of system and its size.

Our primary use case is for telecom customers.

In terms of most valuable features, I'd say Pivotal Greenplum's shared-nothing architecture.

I'd like to see a bridge between Greenplum and Hadoop.

We didn't have any issues yet with stability.

In terms of scalability, I just have one master and two segment hosts.

Initial setup is a little complex. It took around two weeks to deploy.

I prefer an open-source solution but Pivotal Greenplum is cheap and has many functionalities.

On a scale of 1 -10 I'd rate it a 6.

It's super easy to deploy and it also supports different languages and analytics.

As of now, I honestly don't see any room for improvement. I am very happy with this solution, It's helped me a lot.

They should add more analytics. Their documentation could also be improved so that I don't have to bother my coworkers and tech support so often. 

They should advertise more and make it easier for consumers to leave feedback. That way, customers could read the reviews and decide if it's the right solution for them and their needs.

I have been using VMware Tanzu Greenplum for roughly one year.

VMware Tanzu Greenplum is both scalable and stable.

Their technical support is great.

The initial setup is very easy. Deployment took us roughly one or two days.

I would definitely recommend VMware Tanzu Greenplum. It's open-source and the support is great. It's also relatively cheap compared to similar solutions.

Overall, on a scale from one to ten, I would give this solution a rating of ten — I really like it.