VMware Tanzu Data Solutions Reviews

• AMQP protocol
• The simplicity to set up a cluster
• All patterns available (Topic, Routing, RPC, etc.)
• Enables you to provide a response to most problems encountered

I introduced RabbitMQ to my company to bring about more scalability and redirect asynchronous tasks outside of the frontal web servers.

• Scalability was provided by the possibility to add on workers behind RabbitMQ. Asynchronous is the keyword for the message broker.
• I started to split our monolith website and remove all the heavy processes from our web servers.
• Dispatching the workload correctly helped to increase the response time.
• The frontal web server must focus on replying and not on doing reports/PDFs. You must have a dedicated server for this.
• The solution is written in Erlang. Erlang was built for telecommunication systems. One of its assets is that it can upgrade a service in production without downtime. That’s a good point!

• Have more features such as being able to replay a sequence of what was received.
• Handle more messages per second.
• Consume fewer resources: NATS can handle millions of requests within a few minutes. RabbitMQ handles hundreds of requests with the same resources (RAM). Finding a way to be more efficient in this aspect would open them up to other markets, like IoT or embedded systems.

I have used this solution for around two years.

There were no stability issues.

There were no scalability issues.

The documentation from the internet is good.

The setup was pretty straightforward.

I have looked at Apache ActiveMQ and Kafka.

This product is fantastic. Before you use it, make sure you analyze your real needs. In the world of message brokers, there is no single solution. Today, you have solutions that are specialized for specific use cases.

For instance, you have the NATS solution which is another great message broker tool. It is focused on handling a tremendous number of topics and messages per second and it consumes few resources.

However, it’s not as resilient as Kafka. Kafka can replay all the messages received from a date range. However, this one can handle fewer topics.

NATS is written in Golang. Golang is the Go programming language, which I love.

The use case involves the transferring of messages between services. It includes asynchronous messaging and I also need messages flowing to multiple microservices. In this case, it's basically a fan-out mechanism.

RabbitMQ is configurable and quite flexible.

The performance is fast and reliable.

It is easy to use. The addition of more queues and more services can be managed very easily.

There are some security concerns that have been raised with this product.

The configuration works with a config file, where all of the controls, including that of the administrator and user access, are stored there. The security isn't very stringent or very elaborate.

RabbitMQ is a stable solution.

This is a scalable product. There are six or seven services that are connected and using it.

I have not been involved with anything that necessitated contacting the support team.

Previously, we were using MSMQ, which is the Microsoft Message Queuing service. However, with the new version of .NET 4, support for MSMQ was no longer available. We could no longer get the libraries. As a result, we had to switch to a different queue mechanism. 

I have also used Azure Queue.

The initial deployment was quite easy. It took less than half an hour to get it up and running.

I deployed it myself.

The pricing for RabbitMQ is reasonable. It is worth the cost.

We researched ZeroMQ, RabbitMQ, and Kafka. We found that Kafka was a bit of an overkill because our requirements were quite simple. RabbitMQ was pretty easy to set up, which is why we chose it.

My advice for anybody who is implementing this product is to establish your users and exchanges properly.

In general, I'm quite comfortable with RabbitMQ. It satisfies my requirements and the main complaint I have is about the security.

I would rate this solution a seven out of ten.

• Transaction processing between microservices
• Message queue integration with Spring and RPC over Rabbit.

• Quick and simple to implement

• Easy to build proof-of-concept modules based on working examples from Pivotal.

• Out-of-the-box setup and configuration
• Great documentation and support from Pivotal
• Very useful management console

• Difficult to integrate with automated test and CICD 
• Moving beyond basic configurations can be challenging
• Not clear how to implement durable subscriber connections
• Not clear how a Rabbit service restart allows subscriber auto re-connect
• Service cluster failover depends on shared disk infrastructure.

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 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.

• 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!

There are many valuable features, such as parallel loading and the solution's scalability.

It's allowed us to do a lot of data analytics with it that we weren't able to do before.

The performance needs to be improved.

As a whole, two years on multiple versions.

We've had no issues with deployment.

It's stable, but slowness is an issue.

It's scaled find for us.

Customer service is OK.

Technical support is OK.

No solution was used previously.

Implementation was done by a vendor team.

Pricing is pretty much OK compared to others.

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.