VMware Tanzu Data Solutions Reviews

• The publisher and consumer ACK
• High availability
• Queue mirroring
• Exchanges and topics
• Supported programming languages with well-tested libraries

It provides us with a much better scale. We have never lost a single message with RabbitMQ.

The shared RabbitMQ Cluster has improved stability and maintainability of each application. We only have one message bus now.

I want it to reorder messages in a queue, if possible. If you could reorder messages in a queue directly, then you would not need a sequencer to reorder messages outside of RabbitMQ.

I have used this solution for seven years.

There were no stability issues.

There were no scalability issues.

We haven’t needed to use any support yet.

Initially, we were using the BizTalk and Redis solutions. The reason why we switched over was because we were looking for better support in Celery task management and other programming languages. We were looking for a much more stable and secure solution.

It is very simple to set up for basic usage. Clustering is a bit more complex, but it is also easy to do.

The RabbitMQ open source version works fine for almost all the use cases that I came across.

We looked at the Redis solution, but it was not a good fit for our needs.

Read the documentation and follow best practices. Make sure Erlang is up to date!

The most valuable features are MPP and that it's polymorphic.

We have a set of workflow flows that takes 10 hours in Oracle Exadata, now it takes 4 hours with EMC Greenplum.

It doesn't work as efficiently as we'd like because it requires more segment node capacity (size, RAM, CPU) than we currently have.

I've used it since 2013.

At the moment, we don't have any issues with deployment.

At the moment, we don't have any issues with stability.

At the moment, we don't have any issues with scalability.

8/10

8/10

Yes, we have Oracle Exadata.

The initial setup is straightforward. It was simple for our personnel to install on the Unix system and network.

It's a good product when comparing the price to its functionalities.

You should consider the capacity of your data before you buy it.

Our primary use case is as a messaging broker between enterprise applications. It makes for reliable and secure communication.

The most valuable feature for me is that it is open source. The licensing costs are really low and they are transparent. You know how much you are going to pay if you want the commercial version. If you want the open-source version, you do not have to pay anything and that is just as reliable as the commercial one.

I would like to see the performance of the administration portal improved and additional messaging protocols.

I have been working with VMware RabbitMQ for the past eight years.

It is highly stable, reliable, and persistent.

VMware RabbitMQ is definitely scalable.

Technical support is excellent.

Positive

The initial setup was very easy and takes about five minutes to install.

If you want to pay for the licensing it costs eight hundred dollars per CPU core annually with the support.

I would give the following advice prepare a demo, with the vendor and check if it really applies to their needs. I would rate VMware RabbitMQ a nine out of ten.

The most valuable features for us are speed and persistent messaging.

We are now able to leverage real time applications and event driven architecture.

The documentation needs to be improved. There's a learning curve on setting it up and there are issues arising from slower networks that they lack documentation on.

We have been using the product for three years.

Stability issues experienced were only due to a slow network at the client.

We did not encounter any scalability issues.

I never used the technical support.

I am not aware of any previous solutions.

We are a container shop and the only issues during setup were around proper clustering and configuring the application to use it.

We evaluated Apache Kafka also.

I would advise potential customers to use something to wrap their interaction, like Spring for Java.

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 security is great. The interface is nothing special. The support hasn't been that great. You need to go online yourself, to the developer community for support. But apart from that, I think it's fairly secured, quite robust, and stable so far.

Their implementation is quite tricky. It's not that easy to implement RabbitMQ as a cluster. It would be great if they could improve that. 

I have been using RabbitMQ for three years. 

It's quite stable.

It is very scalable. I have a team of 10 developers who are using it and I have some of our clients using it in our Cloud cluster. We have about 10 banks running on the platform now.

I would rate their support as a five out of ten. It has room for major improvement. 

The initial setup is quite straightforward. It can be done within a few hours. 

I would recommend it, but I think there should be a proof of concept for the developer team to get their hands around it and have full control of it before they go into production.

I would rate RabbitMQ a seven out of ten. 

In the next release, I would like for them to improve the UI.

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.

It's a good core database. Scalability and performance are very good. I also like the fact the solution is open-source, so you can use it free of charge.

Some integration with other platforms like design tools, and ETL development tools, that will enable some advanced functionality (like fully down processing, etc.) would be helpful in future releases. Also, if the solution could offer automated creation of DDL statements from power designers, for example, it would be very useful. 

It's a software, and like any software, it has some bugs. However, you can add new features to improve it. Overall, our customers, who are big telcos, have been very satisfied with the platform and with its stability and performance

Scalability is simple because it's an MPP database. If you need more processing power or you need more storage, you just add a few more nodes in the cluster. It works on common commodity hardware. You can use any type of server. You don't need to have proprietary hardware. It's fairly flexible.

The solution requires a minimum amount of downtime when scaling. You can even add additional nodes without any downtime at all. I'm not 100% sure, but I think you can just reconfigure it and the background processes, and Greenplum will do the redistribution of the data.

Technical support is very good. The model they are using to fund the development of their open-source product is via revenue from support for enterprise customers, so they are very attentive when issues arise.

The solution is very straightforward to set up and is also easy to administer and develop using other open-source tools.

It's open-source, so it's free to use.

I'm a partner that works mainly with enterprises. Mostly the partners are big telcos and we deal with tens of terabytes of data.

MPP and columnar databases are the future of the analytical landscape. The era of appliances is over, so implementation of an MPP database on-premises or on the cloud is the way to go. Greenplum is definitely one of the leaders in this area.

I would rate the solution eight out of ten. If they improved the integration with other platforms in the landscape I would rate it higher.