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

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

"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."

"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."

"This is the best tool I have ever used for asynchronous, event-based solutions."

"The most valuable feature of Apache Kafka is the clustering which is very easy to scale and we have multiple servers all over our platforms. It has been useful for stability and performance."

"We are growing and currently, we manage 1M events per second in Kafka."

"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."

"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."

More Apache Kafka pros

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

"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."

"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."

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

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

"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."

"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."

More Red Hat AMQ pros

Cons

"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."

"If you are using the same group ID for multiple topics, it may shut down the application."

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

"The management overhead is more compared to the messaging system. There are challenges here and there. Like for long usage, it requires restarts and nodes from time to time."

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

"For personal preferences, since we use Managed Kafka in AWS, I would appreciate having some kind of UI integrated into Apache Kafka for connecting to it because using code to connect it is basic, but we can use a UI."

"The support from Apache Kafka could improve. Their engineers at times do not know what the solutions can do."

"Lacks elasticity and the ability to scale down."

More Apache Kafka cons

"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."

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

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

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

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

"This product needs better visualization capabilities in general."

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

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

More Red Hat AMQ cons

Pricing and Cost Advice

"It's a premium product, so it is not price-effective for us."

"It is open source software."

"The price for the enterprise version is quite high. For on-premise, there is an annual fee, which starts at 60,000 euros, but it is usually higher than 100,000 euros. The cost for a project including the subscription is usually between 100,000 to 200,000 euros. The cost also depends on the level of support. There are two different levels of support."

"The price of Apache Kafka is good."

"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."

"This is an open-source version."

"Kafka is an open-source solution, so there are no licensing costs."

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

More Apache Kafka pricing and cost advice

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

"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."

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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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