"The solution is very easy to set up."
"The processing power of Apache Kafka is good when you have requirements for high throughput and a large number of consumers."
"Scalability is very good."
"Resiliency is great and also the fact that it handles different data formats."
"valuable features relate to microservices architecture and working on KStream and KSQL DB as a microservices event bus."
"The valuable features are the group community and support."
"The most valuable feature is the support for a high volume of data."
"Robust and delivers messages quickly."
"It's highly scalable. It provides various ways to establish high availability and workloads. E.g., you can spread workloads inside of your clusters."
"The solution is stable."
"RabbitMQ and Kafka require more steps for setup than IBM MQ. Installation of the IBM product is very simple."
"The solution is easy to use and has good performance."
"This initial setup is not complex at all. Deploying it was very easy."
"Clustering is one of its most valuable features."
"Encryption and the fact that we have not had any data loss issues so far have been very valuable features. IBM MQ is well encrypted so that we are well within our compliance and regulatory requirements, so that is a plus point as well."
"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."
"Something that could be improved is having an interface to monitor the consuming rate."
"The initial setup and deployment could be less complex."
"While the solution scales well and easily, you need to understand your future needs and prep for the peaks."
"More adapters for connecting to different systems need to be available."
"They need to have a proper portal to do everything because, at this moment, Kafka is lagging in this regard."
"Kafka does not provide control over the message queue, so we do not know whether we are experiencing lost or duplicate messages."
"would like to see real-time event-based consumption of messages rather than the traditional way through a loop. The traditional messaging system works by listing and looping with a small wait to check to see what the messages are. A push system is where you have something that is ready to receive a message and when the message comes in and hits the partition, it goes straight to the consumer versus the consumer having to pull. I believe this consumer approach is something they are working on and may come in an upcoming release. However, that is message consumption versus message listening."
"The graphical user environment is currently lacking."
"It's hard to put in a nutshell, but it's sort of developed as more of an on-premise solution. It hasn't moved much away from that."
"We have had scalability issues with some projects in the past."
"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."
"It would be nice if we could use the cluster facilities because we are doing active/passive configuration use."
"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 memory management is very poor and it consumes too much memory."
"They could integrate monitoring into the solution, a bit more than they do now. Currently, they have opened the REST API so you can get statistic and accounting information and details from MQ and build your own monitoring, if you want. IBM can improve the solution in this direction."
"Scaling is difficult with IBM MQ."
Apache Kafka is a distributed streaming platform, with the following capabilities:
Apache Kafka gets used for two broad classes of application:
IBM MQ provides the universal messaging backbone for service-oriented architecture (SOA) connectivity. It connects virtually any commercial IT system, whether on premise, in the cloud, or a mixture. For more than 20 years IBM has led the market in messaging middleware and more than 10,000 businesses across all geographies and industries rely on IBM MQ.
Visit for your trial here.
Apache Kafka is ranked 2nd in Message Queue (MQ) Software with 20 reviews while IBM MQ is ranked 1st in Message Queue (MQ) Software with 45 reviews. Apache Kafka is rated 7.8, while IBM MQ is rated 8.0. The top reviewer of Apache Kafka writes "Open source, granular message retention options, and good third party support". On the other hand, the top reviewer of IBM MQ writes "We don't lose messages in transit and we can store messages and forward them when required". Apache Kafka is most compared with ActiveMQ, PubSub+ Event Broker, Red Hat AMQ, Amazon SQS and VMware RabbitMQ, whereas IBM MQ is most compared with VMware RabbitMQ, ActiveMQ, PubSub+ Event Broker, Anypoint MQ and Amazon SQS. See our Apache Kafka vs. IBM MQ report.
See our list of best Message Queue (MQ) Software vendors.
We monitor all Message Queue (MQ) Software reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.