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Apache Kafka vs IBM MQ comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Apr 20, 2025

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

ROI

Sentiment score
7.0
Apache Kafka's ROI benefits include cost savings, quick data insights, increased productivity, and efficient high-traffic data management.
Sentiment score
7.2
Organizations benefit from IBM MQ's data protection, cost efficiency, reliability, and low error frequency, achieving investment recovery within two years.
 

Customer Service

Sentiment score
5.8
Apache Kafka's support stems largely from an open-source community, with varied satisfaction in third-party and enterprise assistance.
Sentiment score
7.0
IBM MQ support receives both praise for efficiency and criticism for slow responses and initial information demands, prompting mixed feedback.
The Apache community provides support for the open-source version.
There is plenty of community support available online.
With containerized flavors of these products, we are having a tough time dealing with PMRs because the versions are new to IBM.
I would rate technical support as an eight.
 

Scalability Issues

Sentiment score
7.8
Apache Kafka's scalability is a major strength, allowing easy horizontal and vertical scaling to meet diverse use case demands.
Sentiment score
7.5
IBM MQ is praised for scalability and adaptability, despite some challenges with legacy dependencies and skills availability.
Customers have not faced issues with user growth or data streaming needs.
IBM MQ handles many thousands of messages in a second, indicating good scalability.
In our environment, we do not have horizontal scaling for IBM MQ, but as demand increases, we would just vertically scale it.
 

Stability Issues

Sentiment score
7.7
Apache Kafka is praised for its resilience and reliability, despite minor configuration challenges and performance under high data volumes.
Sentiment score
8.1
IBM MQ is praised for its stability, reliability, and performance, despite occasional configuration challenges in specific environments.
Apache Kafka is stable.
We have never had any downtime or crashes since it's been running.
The transaction is always guaranteed with IBM MQ, which is the main reason I have been working with it for fifteen years while dealing with financial transactions or messages.
 

Room For Improvement

Apache Kafka needs UI improvements, simplified deployment, reduce ZooKeeper dependency, enhance documentation, client libraries, performance, and advanced features.
IBM MQ needs improved security, a modern interface, better monitoring, seamless cloud integration, competitive pricing, and enhanced message support.
The performance angle is critical, and while it works in milliseconds, the goal is to move towards microseconds.
A more user-friendly interface and better management consoles with improved documentation could be beneficial.
We are always trying to find the best configs, which is a challenge.
Having a graphical user interface would improve usability.
We are dealing with IBM MQ client applications mostly.
 

Setup Cost

Apache Kafka is open-source, but additional provider services can be costly, varying by needs and exceeding 100,000 euros annually.
IBM MQ is expensive but valued for performance and support, justifying costs for large enterprises despite cheaper alternatives.
The open-source version of Apache Kafka results in minimal costs, mainly linked to accessing documentation and limited support.
Its pricing is reasonable.
I am not exactly sure about the licensing cost compared to similar products, but I assume it is affordable since we continue to use it, and it is also used by our customers.
IBM MQ is pretty reasonable when compared to IBM ESB.
 

Valuable Features

Apache Kafka excels in real-time data streaming, scalability, integration, resilience, and handling large volumes with robust message retention.
IBM MQ ensures reliable, secure message delivery with cross-platform compatibility, scalability, and strong integration, favored for banking and enterprise use.
Apache Kafka is effective when dealing with large volumes of data flowing at high speeds, requiring real-time processing.
It allows the use of data in motion, allowing data to propagate from one source to another while it is in motion.
These are financial transactions, so we do not want to lose the message at any cost.
IBM MQ processes many thousands of messages in a second, which is efficient for handling high transaction volumes.
 

Categories and Ranking

Apache Kafka
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
87
Ranking in other categories
Streaming Analytics (8th)
IBM MQ
Average Rating
8.4
Reviews Sentiment
6.9
Number of Reviews
165
Ranking in other categories
Business Activity Monitoring (1st), Message Queue (MQ) Software (1st), Message Oriented Middleware (MOM) (1st)
 

Mindshare comparison

Apache Kafka and IBM MQ aren’t in the same category and serve different purposes. Apache Kafka is designed for Streaming Analytics and holds a mindshare of 2.5%, up 2.0% compared to last year.
IBM MQ, on the other hand, focuses on Message Queue (MQ) Software, holds 25.6% mindshare, up 20.5% since last year.
Streaming Analytics
Message Queue (MQ) Software
 

Q&A Highlights

NC
Sep 04, 2023
 

Featured Reviews

Snehasish Das - PeerSpot reviewer
Data streaming transforms real-time data movement with impressive scalability
I worked with Apache Kafka for customers in the financial industry and OTT platforms. They use Kafka particularly for data streaming. Companies offering movie and entertainment as a service, similar to Netflix, use Kafka Apache Kafka offers unique data streaming. It allows the use of data in…
SelvaKumar4 - PeerSpot reviewer
Offers the ability to batch metadata transfers between systems that support MQ as the communication method
We find it scalable for internal applications, but not so much for external integrations. It should support a wider range of protocols, not just a few specific ones. Many other products have broader protocol support, and IBM MQ is lagging in that area. IBM MQ needs to improve the UI for quicker logging. Users should also have a lot more control over logging, with a dashboard-like interface. That's something they should definitely work on.
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Answers from the Community

NC
Sep 4, 2023
Sep 4, 2023
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 wheth...
2 out of 3 answers
Oct 31, 2021
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.
GT
Sep 14, 2022
The choice depends on your use case.
 

Top Industries

By visitors reading reviews
Financial Services Firm
31%
Computer Software Company
12%
Manufacturing Company
7%
Retailer
6%
Financial Services Firm
37%
Computer Software Company
12%
Manufacturing Company
7%
Government
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What are the differences between Apache Kafka and IBM MQ?
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 user...
What do you like most about Apache Kafka?
Apache Kafka is an open-source solution that can be used for messaging or event processing.
What is your experience regarding pricing and costs for Apache Kafka?
Its pricing is reasonable. It's not always about cost, but about meeting specific needs.
What is MQ software?
Hi As someone with 45+ years of experience in the Transaction and Message Processing world, I have seen many "MQ" solutions that have come into the market place. From my perspective, while each pro...
How does IBM MQ compare with VMware RabbitMQ?
IBM MQ has a great reputation behind it, and this solution is very robust with great stability. It is easy to use, simple to configure and integrates well with our enterprise ecosystem and protocol...
What do you like most about IBM MQ?
The feature I find most effective for ensuring message delivery without loss is the backup threshold. This feature allows for automatic retries of transactional messages within a specified threshold.
 

Comparisons

 

Also Known As

No data available
WebSphere MQ
 

Overview

 

Sample Customers

Uber, Netflix, Activision, Spotify, Slack, Pinterest
Deutsche Bahn, Bon-Ton, WestJet, ARBURG, Northern Territory Government, Tata Steel Europe, Sharp Corporation
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