We performed a comparison between Apache Kafka and IBM MQ based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Both products are moderately easy to install, robust, and high-performing. The main advantage of Apache Kafka is that it is free of charge but still offers adequate technical support solutions.
"With Kafka, events and streaming are persistent, and multiple subscribers can consume the data. This is an advantage of Kafka compared to simple queue-based solutions."
"The high availability is valuable. It is robust, and we can rely on it for a huge amount of data."
"The valuable features are the group community and support."
"Its availability is brilliant."
"The open-source version is relatively straightforward to set up and only takes a few minutes."
"I have seen a return on investment with this solution."
"Apache Kafka has good integration capabilities and has plenty of adapters in its ecosystem if you want to build something. There are adapters for many platforms, such as Java, Azure, and Microsoft's ecosystem. Other solutions, such as Pulsar have fewer adapters available."
"For example, when you want to send a message to inform all your clients about a new feature, you can publish that message to a single topic in Apache Kafka. This allows all clients subscribed to that topic to receive the message. On the other hand, if you need to send billing information to a specific customer, you can publish that message on a topic dedicated to that customer. This message can then be sent as an SMS to the customer, allowing them to view it on their mobile device."
"IBM is still adding some features and coding some other systems on the security end. However, it has the most security features I've seen in a communication solution. Security is the most important thing for our purposes."
"The solution allows one to easily configure an IBM MQQueueManager."
"The high availability and session recovery are the most valuable features because we need the solution live all day."
"The scalability of IBM MQ is good."
"I like the MQ's simplicity and rock-solid stability. I've never experienced a failure in two decades caused by the product itself. It has only failed due to human error."
"The first things are its simplicity and its robustness. Compared to any other product, it's the most robust I've worked with. And it's extremely easy to manage."
"The solution is very easy to work with."
"All the features are valuable."
"One complexity that I faced with the tool stems from the fact that since it is not kind of a stand-alone application, it won't integrate with native cloud, like AWS or Azure."
"Kafka 2.0 has been released for over a month, and I wanted to try out the new features. However, the configuration is a little bit complicated: Kafka Broker, Kafka Manager, ZooKeeper Servers, etc."
"Too much dependency on the zookeeper and leader selection is still the bottleneck for Kafka implementation."
"An area for improvement would be growth."
"Kafka is a nightmare to administer."
"The repository isn't working very well. It's not user friendly."
"More Windows support, I believe, is one area where it can improve."
"The solution can improve by having automation for developers. We have done many manual calculations and it has been difficult but if it was automated it would be much better."
"While there is support for API, it's not like the modern API capabilities."
"I would like to see faster monitoring tools for this solution."
"In terms of volume, it is not able to handle a huge volume. We also have limitations of queues related to IBM MQ. We often need to handle a very big volume, but currently we do have limitations. If those kinds of limitations could be relaxed, it would help us to work better."
"Customer support response times could be improved."
"IBM HQ's scalability isn't the best."
"In the next release, I would like for there to be easier monitoring. The UI should be easier for non-technical users to set up appliances and servers."
"The solution requires a lot of work to implement and maintain."
"SonicMQ CAA (continuous availability architecture) functionality on auto failover and data persistence should be made available without a shared drive, as it exists in multi-instance queue managers."
Apache Kafka is ranked 1st in Message Queue (MQ) Software with 78 reviews while IBM MQ is ranked 2nd in Message Queue (MQ) Software with 158 reviews. Apache Kafka is rated 8.0, while IBM MQ is rated 8.4. The top reviewer of Apache Kafka writes "Real-time processing and reliable for data integrity". On the other hand, the top reviewer of IBM MQ writes "Offers the ability to batch metadata transfers between systems that support MQ as the communication method". Apache Kafka is most compared with Amazon SQS, Red Hat AMQ, Anypoint MQ, PubSub+ Event Broker and VMware Tanzu Data Services, whereas IBM MQ is most compared with ActiveMQ, VMware Tanzu Data Services, Red Hat AMQ, PubSub+ Event Broker and Anypoint MQ. See our Apache Kafka vs. IBM MQ report.
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It is like comparing apples to oranges. Mq is focus on enabling the communication between two different programs in different systems and guaranteeing the delivery of the messages where Kafka has specialized on the generation of events by a source system that are catch by "listener" programs.
MQ is point to point, if the receiving program reads the message from the queue, it dissapears, in the case of Kafka as the event is read by a "listener" program, the event is still there as there could be more then one program that has subscribed to the so called "topic".
So, as mention in another answer, it depends from the use case. If you have for example a front end program that communicated with a very bad bandwith to another program and you have to send critical data, the best solution could be MQ. If you have an "card stolen" application that needs to alert different systems, you could publish the "stolen" event in the front end app and have any number of system listening to this event.
Of course it is also valid the argument that Kafka is open source and IBM MQ is propietary but if you are considering a production environment you can find different vendors (including IBM) that provide products based on Kafka open source.
Apache Kafka is open source and can be used for free. It has very good log management and has a way to store the data used for analytics. Apache Kafka is very good if you have a high number of users. This tool has great scalability with high throughput and a very helpful supportive online community.
However, Kafka does not provide control over the message queue, so it is difficult to know whether messages are being delivered, lost, or duplicated. We would like to see more adapters for connecting to different systems made available. I think this would be a better product if the graphical user interface was easier. The manual calculations needed for this solution can be difficult. If the process was automated, it would be a much better product.
IBM MQ has a very strong reputation and is very robust with great stability. This solution is easy to use, simple to configure, and integrates well with our enterprise ecosystem and protocols. IBM ensures message delivery. You can track and trace everything. If a message doesn’t arrive at its destination, it will go back to the queue; this ensures no message is ever lost. This is a huge selling point for us.
IBM MQ does not handle huge volume very well, though. There are some limitations to the queues. If these limitations could be relaxed, it would be a better product for us. You have to license per application and installation, so scaling up can get very costly very quickly.
Conclusion
Apache Kafka is a cost-effective solution for high-volume, multi-source data collection. If you are in a high-growth trajectory and if total message accountability and tracking is not a huge issue for you, this solution may work well for you.
IBM MQ is a licensed product and can be very expensive, it also does not scale easily, which can be very problematic. IBM MQ requires a definite skillset that not many people have, which can be an issue for some and it affects the fast responsive support of this solution.