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

Download the report

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.

To learn more, read our detailed Streaming Analytics Report (Updated: July 2026).

Buyer's Guide

Streaming Analytics

July 2026

Download the complete report

Helped 908,834 peers since 2012

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.

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

"Apache Kafka has helped out the organization because we leverage it for all our eCommerce real-time analytics use cases."

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

"I have seen a return on investment with this solution."

"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."

"This is a system for email and other small devices, and there has been a relay of transactions continuously over the last two years it has been in production."

"Apache Kafka is very useful in our organization and makes applications more loosely coupled."

"When comparing it with other messaging and integration platforms, this is one of the best rated."

"I appreciate that Apache Kafka is fast and secure thanks to implementing it with AWS, allowing me to secure it on a high level."

More Apache Kafka pros

"The most valuable feature is stability."

"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."

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

"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."

"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 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 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."

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

More Red Hat AMQ pros

Cons

"The initial setup and deployment could be less complex."

"For the original Kafka, there is room for improvement in terms of latency spikes and resource consumption. It consumes a lot of memory."

"I suggest using cloud services because the solution is expensive if you are using it on-premises."

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

"Maintaining and configuring Apache Kafka can be challenging, especially when you want to fine-tune its behavior."

"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."

"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."

"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."

More Apache Kafka cons

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

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

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

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

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

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

"This product needs better visualization capabilities in general."

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

More Red Hat AMQ cons

Pricing and Cost Advice

"Apache Kafka has an open-source pricing."

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

"When starting to look at a distributed message system, look for a cloud solution first. It is an easier entry point than an on-premises hardware solution."

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

"It's quite affordable considering the value it provides."

"We use the free version."

"Apache Kafka is an open-sourced solution. There are fees if you want the support, and I would recommend it for enterprises. There are annual subscriptions available."

"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."

More Apache Kafka pricing and cost advice

"The solution is open-source."

"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."

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

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

See which vendors are best for you

Use our free recommendation engine to learn which Streaming Analytics solutions are best for your needs.

See recommendations

908,834 professionals have used our research since 2012.

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

Find out what your peers are saying about Databricks, Microsoft, Apache and others in Streaming Analytics. Updated: July 2026.

DOWNLOAD NOW

908,834 professionals have used our research since 2012.

We monitor all Streaming Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.