Apache Kafka vs Red Hat AMQ comparison

Why PeerSpot?

The compared Apache and Red Hat solutions aren't in the same category. Apache is ranked #6 in SA , with an average rating of 8.6, and holds a 3.5% mindshare in the category. Red Hat is ranked #7 in MQ , with an average rating of 9.0, and holds a 5.2% 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

7,712 Views
4,010 Comparison Views

96% willing to recommend

Red Hat AMQ

Read 10 Red Hat AMQ reviews

2,638 Views
2,084 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

6.9

Number of Reviews

Ranking in other categories

Streaming Analytics (6th)

Red Hat AMQ

Average Rating

8.2

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Message Queue (MQ) Software (7th)

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 3.5%, down 3.8% compared to last year.
Red Hat AMQ, on the other hand, focuses on Message Queue (MQ) Software, holds 5.2% mindshare, down 9.6% since last year.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Apache Kafka	3.5%
Databricks	7.4%
Apache Flink	6.7%
Other	82.4%

Streaming Analytics

Message Queue (MQ) Software Mindshare Distribution
Product	Mindshare (%)
Red Hat AMQ	5.2%
IBM MQ	21.4%
ActiveMQ	20.1%
Other	53.3%

Message Queue (MQ) Software

Featured Reviews

Amandeep Pawar

Engineer Technology at Iris 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

"Apache Kafka has became our main component on almost all our distributed solutions."

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

"The message bus capabilities, basically sending messages to it, and the way it handles events or messages is pretty good."

"The solution is scalable, and we have over a thousand users using this solution and will most likely increase the number of users because we have tested 100,000 messages per second, which is impressive."

"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."

"Ease of use."

"It is easy to configure."

"It is a stable solution...A lot of my experience indicates that Apache Kafka is scalable."

More Apache Kafka pros

"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."

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

"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."

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

"The self-service aspect is very important for us, and AMQ Streams has enabled us to deliver new services faster, going from days to hours."

"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."

More Red Hat AMQ pros

Cons

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

"There is a lot of information available for the solution and it can be overwhelming to sort through."

"It needs a separate cluster and a separate administrator to manage the Kafka cluster, adding an extra cost."

"Apache Kafka can improve by providing a UI for monitoring. There are third-party tools that can do it, but it would be nice if it was already embedded within Apache Kafka."

"The UI is based on command line. It would be helpful if they could come up with a simpler user interface."

"There are some latency problems with Kafka."

"There have been some challenges with monitoring Apache Kafka, as there are currently only a few production-grade solutions available, which are all under enterprise license and therefore not easily accessible. The speaker has not had access to any of these solutions and has instead relied on tools, such as Dynatrace, which do not provide sufficient insight into the Apache Kafka system. While there are other tools available, they do not offer the same level of real-time data as enterprise solutions."

"We struggled a bit with the built-in data transformations because it was a challenge to get them up and running the way we wanted."

More Apache Kafka cons

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

"The areas for improvement include cost, which is a primary concern."

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

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

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

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

"There are some aspects of the monitoring that could be improved on."

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

More Red Hat AMQ cons

Pricing and Cost Advice

"Apache Kafka is open-source and can be used free of charge."

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

"I rate Apache Kafka's pricing a five on a scale of one to ten, where one is cheap and ten is expensive. There are no additional costs apart from the licensing fees for Apache Kafka."

"It is approximately $600,000 USD."

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

"Apache Kafka is free."

"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."

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

More Apache Kafka pricing and cost advice

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

"The solution is open-source."

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

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Outsourcing Company

13%

Manufacturing Company

10%

Construction Company

Financial Services Firm

15%

Outsourcing Company

10%

Manufacturing Company

Government

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?

Based on my understanding for the setup and cost to set up Apache Kafka, I was not responsible for the pricing or licensing decisions. Apache Kafka itself is open source and free to use. Infrastruc...

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What needs improvement with Apache Kafka?

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

Azure Stream Analytics vs Apache Kafka

Compared 8% of the time

Databricks vs Apache Kafka

Compared 7% of the time

IBM MQ vs Apache Kafka

Compared 7% of the time

MuleSoft Anypoint Platform 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 17% of the time

VMware Tanzu Data Solutions vs Red Hat AMQ

Compared 15% of the time

IBM Event Streams vs Red Hat AMQ

Compared 11% 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

October 2026

Download Apache Kafka product report

Buyer's Guide

Red Hat AMQ

October 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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