During my company's evaluation process for other options from Apache Kafka, we came across RabbitMQ. My company chose Apache Kafka over RabbitMQ since it was one of the market's more popular tools. With Apache Kafka, more materials, support, online technical groups, and forums were available for consumers.

Redis has an open-source solution, but I'm not sure about IBM. I haven't researched it. 

There were other solutions, like Apache MQ, but there were a number of components we looked at that were based around being a message bus, and Kafka was the winner from that review work.

There are other options. For example, Databricks is a Kafka alternative. We decided to go with Kafka because one of our clients already chose Kafka.

While evaluating, we found out Databricks is more expensive, for the level of activity that Kafka handles (in this case, millions of requests per day). Databricks could do it, but it would be overly expensive.

I would rate Apache Kafka's pricing a seven out of ten, with one being cheap and 10 being very expensive.

I did not evaluate other solutions.

We evaluated multiple options, such as ActiveMQ and RabbitMQ. We leaned towards this solution.

MQ messaging systems are not my core strength but for any integration platform where we have a large number of APIs and events, to integrate with an IoT platform, for example, I found Kafka is better than ActiveMQ.

I'm not getting into in MQTT or other things but comparatively, when you compare ActiveMQ and Kafka, Kafka has done better.

There is a competing open-source solution called NATS but I see that Apache Kafka is widely used in many places.

Performance-wise, Kafka is better than any of the other products.

We looked at RabbitMQ and Spark Streaming.

I'm not the product owner, so I didn't have a say in what should be chosen. We were seeing a high throughput with Kafka which is why we ultimately chose it.

We evaluated AWS Kinesis as well.

VMware RabbitMQ and ActiveMQ are products that are not being used by us. I wanted to look into it. But we use different things.

We compared our findings to those of other researchers. We are primarily concerned with performance. Kafka is unquestionably the performance leader.

We did not evaluate other options as Apache Kafka is the standard.

The client evaluated alternatives before I arrived, but I was not there during the evaluation so I cannot comment.

We used Akka Streams for faster communication, but it would require additional configuration and setup for persistence. Kafka provides those by default.

We didn't evaluate any other options.

We didn't evaluate other options, as we already had a positive experience across the team with Kafka. Everybody agreed to work with it.

We were considering Kinesis too, since we were running on AWS. We preferred to opt for a tool with which people were more familiar.

Before choosing this product, we did not evaluate other options.

We did not look at anything else. At that time, this was already accepted by the industry for streaming data processing.

We unsuccessfully, and kind of foolishly, tried Apache Camel. They were not similar in services, so we moved to Kafka rightfully, and then to AWS cloud ultimately.

My customer has asked me to choose between IBM MQ and Apache Kafka. I will be comparing these two solutions in the near future. My impression is that Kafka is going to better suit my customer, but I have to consider their specific needs before I can be sure.