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 8.7, and holds a 3.8% mindshare in the category. Red Hat is ranked #8 in MQ , with an average rating of 9.0, and holds a 5.8% 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

6,471 Views
3,106 Comparison Views

96% willing to recommend

Red Hat AMQ

Read 10 Red Hat AMQ reviews

2,337 Views
1,799 Comparison Views

90% willing to recommend

Apache Kafka

Red Hat AMQ

Comparison Buyer's Guide

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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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July 2026

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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

6.9

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 3.8%, up 3.5% compared to last year.
Red Hat AMQ, on the other hand, focuses on Message Queue (MQ) Software, holds 5.8% mindshare, down 9.4% since last year.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Apache Kafka	3.8%
Databricks	7.5%
Apache Flink	7.5%
Other	81.2%

Streaming Analytics

Message Queue (MQ) Software Mindshare Distribution
Product	Mindshare (%)
Red Hat AMQ	5.8%
IBM MQ	21.0%
ActiveMQ	20.1%
Other	53.099999999999994%

Message Queue (MQ) Software

Featured Reviews

Amandeep Pawar

Senior Engineer at Airy Software Technologies Private Limited

Event-driven architecture has improved asynchronous communication and supports high throughput

We can improve the high throughput because there are some limitations. We could add something to improve Apache Kafka. Based on my daily usage and analysis, there is a complex setup and management, which is one area requiring improvement. Apache Kafka does not have built-in message delay or scheduling capabilities. Apache Kafka cannot natively schedule messages. Limited message prioritization is also an area requiring improvement. Ordering is limited to a single partition. Large messages affect performance. Apache Kafka is optimized for many small to medium-sized messages, but large payloads increase network usage, increase disk usage, and slow down producers and consumers. I rate Apache Kafka eight out of ten instead of ten out of ten because operating an Apache Kafka cluster requires expertise in partitioning, application monitoring, and capacity planning. Self-managed deployment can become complex as the cluster grows. Pro-managed Apache Kafka services significantly reduce the operational overhead.

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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

"Supports more than 10,000 events/second, scalability, and replication, and it is a good product for event-driven architecture."

"Excellent speeds for publishing messages faster."

"It seemed pretty stable and didn't have any issues at all."

"As a software developer, I have found Apache Kafka's support to be the most valuable...The solution is easy to integrate with any of our systems."

"The stability is very nice, and we currently manage 50 million events daily."

"The open-source version is relatively straightforward to set up and only takes a few minutes."

"It's an open-source product, which means it doesn't cost us anything to use it."

"The processing power of Apache Kafka is good when you have requirements for high throughput and a large number of consumers."

More Apache Kafka pros

"This product is well adopted on the OpenShift platform. For organizations like ours that use OpenShift for many of our products, this is a good feature."

"From the functionality perspective, 3scale provides a very comparable, if not the same feature set as any leader in the market for API management and the gateway perspective, but with a fraction of the price."

"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."

"Reliability is the main criterion for selecting this tool for one of the busiest airports in Mumbai."

"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."

"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."

More Red Hat AMQ pros

Cons

"The solution's initial setup process was complex."

"The product is good, but it needs implementation and on-going support. The whole cloud engagement model has made the adoption of Kafka better due to PaaS (Amazon Kinesis, a fully managed service by AWS)."

"Apache Kafka has performance issues that cause it to lag."

"There are some latency problems with Kafka."

"The third party is not very stable and sometimes you have problems with this component. There are some developments in newer versions and we're about to try them out, but I'm not sure if it closes the gap."

"As an open-source project, Kafka is still fairly young and has not yet built out the stability and features that other open-source projects have acquired over the many years. If done correctly, Kafka can also take over the stream-processing space that technologies such as Apache Storm cover."

"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."

"We can improve the high throughput because there are some limitations."

More Apache Kafka cons

"The turnaround of adopting new versions of underlying technologies sometimes is too slow."

"This solution is completely unstable. We lose messages."

"This product needs better visualization capabilities in general."

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

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

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

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

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

More Red Hat AMQ cons

Pricing and Cost Advice

"It's a bit cheaper compared to other Q applications."

"Apache Kafka has an open-source pricing."

"This is an open-source solution and is free to use."

"The cost can vary depending on the provider and the specific flavor or version you use. I'm not very knowledgeable about the pricing details."

"It is approximately $600,000 USD."

"The solution is open source."

"We are using the free version of Apache Kafka."

"It is open source software."

More Apache Kafka pricing and cost advice

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

"The solution is open-source."

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

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

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

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Outsourcing Company

12%

Manufacturing Company

10%

Construction Company

Financial Services Firm

18%

Manufacturing Company

10%

Government

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	33
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...

See all answers

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 12% 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

IBM MQ vs Red Hat AMQ

Compared 19% of the time

ActiveMQ vs Red Hat AMQ

Compared 18% of the time

VMware Tanzu Data Solutions vs Red Hat AMQ

Compared 12% of the time

IBM Event Streams vs Red Hat AMQ

Compared 11% of the time

Amazon SQS vs Red Hat AMQ

Compared 7% of the time

More Red Hat AMQ Competitors

Product Reports

Buyer's Guide

Apache Kafka

August 2026

Download Apache Kafka product report

Buyer's Guide

Red Hat AMQ

July 2026

Download Red Hat AMQ product report

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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