Apache Kafka vs Red Hat AMQ comparison

The compared Apache and Red Hat solutions aren't in the same category. Apache is ranked #3 in SA , with an average rating of 8.8, and holds a 3.9% mindshare in the category. Red Hat is ranked #8 in MQ , with an average rating of 8.5, and holds a 6.4% mindshare. Additionally, 96% of Apache users are willing to recommend the solution, compared to 90% of Red Hat users who would recommend it.

Apache Kafka

Read 92 Apache Kafka reviews

5,785 Views
2,488 Comparison Views

96% willing to recommend

Red Hat AMQ

Read 10 Red Hat AMQ reviews

2,219 Views
1,686 Comparison Views

90% willing to recommend

Apache Kafka

Red Hat AMQ

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Executive SummaryUpdated on Feb 8, 2026

Red Hat AMQ and Apache Kafka both compete in the messaging and event streaming domain. Apache Kafka is perceived as the superior product due to its robust features, primarily in handling larger data volumes and community support.

Features: Red Hat AMQ's features include strong integration capabilities with existing Red Hat products, a focus on security through user authentication and authorization features, and enterprise support. Apache Kafka offers high throughput, scalability, and flexibility in message processing, along with a comprehensive ecosystem and community support, making it highly adaptable to various use cases.

Room for Improvement: Red Hat AMQ can improve in terms of documentation to facilitate better understanding by new users and potentially enhance throughput performance. It could also benefit from increasing its community engagement to broaden user support. Apache Kafka may enhance its out-of-box security features and streamline management to cater more to users in non-tech roles. Additionally, better integration features with non-Kafka environments could be beneficial.

Ease of Deployment and Customer Service: Apache Kafka offers straightforward deployment with broad community support assisting in its complexity management. Red Hat AMQ is favored for its seamless integration within the Red Hat suite, supported by responsive customer service. Both benefit from extensive documentation, but Kafka's active community further enhances deployment experiences for tech-savvy teams.

Pricing and ROI: Red Hat AMQ delivers competitive and predictable pricing, promising ROI within the Red Hat ecosystem due to its integration capabilities. Apache Kafka, although it may have higher upfront costs, offers substantial ROI through its performance and scalability over time. Its ability to handle significant data volumes and integrate diverse applications often justifies its initial investment.

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Review summaries and opinions

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

Categories and Ranking

Apache Kafka

Average Rating

8.2

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Streaming Analytics (3rd)

Red Hat AMQ

Average Rating

8.2

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Message Queue (MQ) Software (8th)

Mindshare comparison

Apache Kafka and Red Hat AMQ aren’t in the same category and serve different purposes. Apache Kafka is designed for Streaming Analytics and holds a mindshare of 3.9%, up 3.0% compared to last year.
Red Hat AMQ, on the other hand, focuses on Message Queue (MQ) Software, holds 6.4% mindshare, down 9.6% since last year.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Apache Kafka	3.9%
Apache Flink	8.2%
Databricks	7.9%
Other	80.0%

Streaming Analytics

Message Queue (MQ) Software Mindshare Distribution
Product	Mindshare (%)
Red Hat AMQ	6.4%
IBM MQ	20.7%
ActiveMQ	19.8%
Other	53.099999999999994%

Message Queue (MQ) Software

Featured Reviews

Varuns Ug

Senior Software Developer at NIT

Event-driven workflows have improved payment processing and reduced latency across services

One area for improvement in Apache Kafka is operational complexity. Running and maintaining an Apache Kafka cluster at scale involves handling partitions, replications, retention policies, rebalancing, and monitoring, which requires strong expertise. Debugging and observability can be complex in large systems, as troubleshooting issues such as consumer lag, offset management problems, or uneven partition distribution can become challenging. The learning curve is relatively steep, requiring a good understanding of concepts such as partition, consumer group, offset commit, and delivery guarantees to avoid subtle production issues. One area where Apache Kafka could improve is the developer experience around debugging and tracing events end to end. In distributed systems, when an event passes through multiple topics and consumer services, troubleshooting can become time-consuming. Better built-in observability for tracing event flows across services would be very useful.

Read full review

SachinJain

Senior Technical Specialist at Intuitive Technology Partners

Efficiently manages high availability and fault tolerance for critical systems with user-friendly management features

I have experience with features such as message persistence and fault tolerance because I configured high availability and fault tolerance for the client environment, including active-active and active-passive configurations. I mainly prefer active-active. I created a security feature for user authentication and authorization in Red Hat AMQ using vault. When you enable the vault, then your whole Red Hat AMQ becomes more secure. Management is straightforward. I configured it and created documentation. The operations team takes care of the operation part. I educate them on how to manage access, so they can easily add new people who join the company or manage the people who leave. The benefits of using Red Hat AMQ include easy configuration and monitoring. On the portal, I can monitor how many packets or alerts have been generated or sent to the end user via Red Hat AMQ along with messages or emails. It also shows utilization in the tool. These features also come with other AMQs such as Amazon and IBM.

Read full review

Quotes from Members

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

Pros

"It is the performance that is really meaningful."

"Kafka allows you to handle huge amounts of data and classify it into different categories. If you have huge amounts of data, Kafka is a very good solution for data classification."

"Kafka was at the base of our system architecture."

"There are numerous possibilities that can be explored. While it may be challenging to fully comprehend the potential advantages, one key aspect is the ability to establish a proper sequence of events rather than simply dealing with a jumbled group of occurrences. These events possess their own timestamps, even if they were not initially provided with one, and are arranged in a chronological order that allows for a clear understanding of the progression of the events."

"I use it for real-time processing workloads. So, in some instances, it's like IoT data. We need to put it into a data lake."

"Apache Kafka has helped our client's online restaurant company by allowing them to take any orders and send the notifications with some other details, such as logic commands, to the different microservices."

"The most valuable feature of Apache Kafka is its versatility. It can solve many use cases or can be a part of many use cases. Its fundamental value of it is in the real-time processing capability."

"The ability to partition data on Kafka is valuable."

More Apache Kafka pros

"The most valuable feature for us is the operator-based automation that is provided by Streams for infrastructure as well as user and topic management. This saves a lot of time and effort on our part to provide infrastructure. For example, the deployment of infrastructure is reduced from approximately a week to a day."

"The benefits of using Red Hat AMQ include easy configuration and monitoring; on the portal, I can monitor how many packets or alerts have been generated or sent to the end user via Red Hat AMQ along with messages or emails, and it also shows utilization in the tool."

"The solution is very lightweight, easy to configure, simple to manage, and robust since it launched."

"The most valuable feature is stability."

"I can organize the tool with microservices, which allows me to use it across different services. It is easy to learn."

"My impression is that it is average in terms of scalability."

"Red Hat AMQ's best feature is its reliability."

"AMQ is highly scalable and performs well. It can process a large volume of messages in one second. AMQ and OpenShift are a good combination."

More Red Hat AMQ pros

Cons

"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."

"I would like them to reduce the learning curve around the creation of brokers and topics. They also need to improve on the concept of the partitions."

"Apache Kafka can improve by making the documentation more user-friendly."

"The management tool could be improved."

"Confluent has improved aspects like documentation and cloud support, yet Kafka's reliance on older architectures like ZooKeeper in previous versions is a limitation."

"Config management can be better. We are always trying to find the best configs, which is a challenge."

"Kafka does not provide control over the message queue, so we do not know whether we are experiencing lost or duplicate messages."

More Apache Kafka cons

"Red Hat AMQ's cost could be improved, and it could have better integration."

"AMQ could be better integrated with Jira and patch management tools."

"There are several areas in this solution that need improvement, including clustering multi-nodes and message ordering."

"There are some aspects of the monitoring that could be improved on. There is a tool that is somewhat connected to Kafka called Service Registry. This is a product by Red Hat that I would like to see integrated more tightly."

"The product needs to improve its documentation and training."

"This product needs better visualization capabilities in general."

"The challenge is the multiple components it has. This brings a higher complexity compared to IBM MQ, which is a single complete unit."

"There is improvement needed to keep the support libraries updated."

More Red Hat AMQ cons

Pricing and Cost Advice

"Apache Kafka has an open-source pricing."

"The solution is free, it is open-source."

"Kafka is open-source and it is cheaper than any other product."

"The solution is open source; it's free to use."

"This is an open-source version."

"I would not subscribe to the Confluent platform, but rather stay on the free open source version. The extra cost wasn't justified."

"It is approximately $600,000 USD."

"Kafka is more reasonably priced than IBM MQ."

More Apache Kafka pricing and cost advice

"This is a very cost-effective solution and the pricing is much better than competitors."

"I would rate the pricing a six out of ten, with ten being expensive."

"There is a subscription needed for this solution and there are support plans available."

"The solution is open-source."

"Red Hat AMQ's pricing could be improved."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Manufacturing Company

10%

Computer Software Company

Outsourcing Company

Financial Services Firm

19%

Manufacturing Company

10%

Government

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	32
Midsize Enterprise	20
Large Enterprise	51

By reviewers
Company Size	Count
Small Business	5
Midsize Enterprise	4
Large Enterprise	2

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...

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What is your experience regarding pricing and costs for Apache Kafka?

From the AWS perspective, the price is on the higher side. However, if you go for Apache Kafka, it is low. From a price perspective, if you are asking about Apache Kafka, I would rate it a nine.

See all answers

What needs improvement with Apache Kafka?

Apache Kafka is abundant with features which only an expert-level person will be able to manage due to the high volume and high concurrent expectations. Apache Kafka groups could introduce themes o...

See all answers

What needs improvement with Red Hat AMQ?

The areas for improvement include cost, which is a primary concern. The deployment process is simple, but the cost is very important. Additionally, the management portal should be more user-friendl...

See all answers

What is your primary use case for Red Hat AMQ?

For use cases for Red Hat AMQ, let's take banking purposes. This depends upon the firm or the service or product company. For example, let's take HDFC Bank or any other bank. Whenever a customer de...

See all answers

What advice do you have for others considering Red Hat AMQ?

I work primarily with Red Hat. For IBM, I have worked with their channel partner, not directly with IBM. For Amazon, I work with partners only. I am working with one company as a consultant. I also...

See all answers

Comparisons

PubSub+ Platform vs Apache Kafka

Compared 11% of the time

Databricks vs Apache Kafka

Compared 10% of the time

Azure Stream Analytics vs Apache Kafka

Compared 10% of the time

IBM MQ vs Apache Kafka

Compared 8% of the time

Apache Pulsar vs Apache Kafka

Compared 6% of the time

More Apache Kafka Competitors

ActiveMQ vs Red Hat AMQ

Compared 19% of the time

IBM MQ vs Red Hat AMQ

Compared 18% of the time

VMware Tanzu Data Solutions vs Red Hat AMQ

Compared 13% of the time

IBM Event Streams vs Red Hat AMQ

Compared 10% of the time

Amazon SQS vs Red Hat AMQ

Compared 6% of the time

More Red Hat AMQ Competitors

Product Reports

Buyer's Guide

Apache Kafka

June 2026

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Buyer's Guide

Red Hat AMQ

June 2026

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Also Known As

No data available

Red Hat JBoss A-MQ, Red Hat JBoss AMQ

Overview

Apache Kafka provides scalable, high-throughput, real-time data processing. Appreciated for its open-source nature and integration capabilities, Kafka supports distributed messaging and high-volume handling with essential features like message retention, replication, and partitioning.

Apache Kafka is a powerful tool for managing efficient data streams and high volumes of asynchronous messages. Its ease of setup and robust integration options make it popular among industries requiring real-time data streaming and processing. Key features such as message retention and consumer groups cater to demanding applications, while fault-tolerant design ensures reliability. Despite its advantages, Kafka can improve in areas like duplicate management, documentation, and intuitive interfaces. Challenges in configuration and monitoring tools suggest areas for enhancement, alongside reducing complexity and resource dependency.

What are the key features of Apache Kafka?

Scalability: Efficiently handles increasing data volumes without performance loss.
High Throughput: Processes large amounts of data quickly and efficiently.
Real-time Processing: Facilitates immediate data streaming and analytics.
Fault Tolerance: Maintains operations despite failures, ensuring continuous data flow.
Open-source Nature: Offers community-driven enhancements and reduced costs.

What benefits should users look for in Apache Kafka reviews?

Robust Integration: Easily connects with various applications and systems.
Cost-effectiveness: Leverages open-source advantages for financial savings.
Reliability: Provides consistent performance with fault-tolerant mechanisms.
Scalable Infrastructure: Supports growing business needs without compromising efficiency.

Industry applications for Apache Kafka include real-time data streaming for IoT, big data management, and analytics. In finance, it supports fraud detection and transaction monitoring. Healthcare uses Kafka for patient data handling and logistics leverage its data distribution capabilities to optimize operations. Its ability to manage large-scale asynchronous communication makes it vital across sectors demanding high data throughput and reliability.

Apache

Red Hat AMQ provides robust performance with high scalability and security, supporting efficient message processing and various protocols. It integrates with OpenShift and Apache Kafka, making it ideal for event-driven microservices in hybrid environments.

Red Hat AMQ is designed for asynchronous messaging, data synchronization, and real-time notifications. Its strengths include high availability, fault tolerance, and operator-based automation. The lightweight, scalable design enables straightforward management, combined with reliable official support. Integration with ActiveMQ ensures stable and independent installation. Users can also employ connectors and routing on Kubernetes, enhancing its utility for sectors like banking and logistics.

What are the most valuable features of Red Hat AMQ?

Compatibility with OpenShift, facilitating seamless integration
Operator-based automation for streamlined processes
High availability and fault tolerance for continuous operations
Vault-based security ensuring data protection
Scalability and lightweight design for efficient resource use
Support for multiple protocols enhancing flexibility

What benefits should users look for when evaluating Red Hat AMQ?

Scalability for growing business demands
Ease of configuration reducing setup time
Robust performance delivering reliable message processing
Cost advantages offering economic benefits over competitors
Stability from independent installation ensuring resilience

Industries use Red Hat AMQ for asynchronous application messaging, enhancing communication in Master System Integration projects. Sectors like banking utilize it for real-time alerts, while logistics companies leverage it for notifications. Its support for connectors and routing within OpenShift benefits organizations with complex data flow requirements.

Red Hat

Sample Customers

Uber, Netflix, Activision, Spotify, Slack, Pinterest

E*TRADE, CERN, CenturyLink, AECOM, Sabre Holdings

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