ActiveMQ vs Apache Kafka comparison

The compared ActiveMQ and Apache Kafka solutions aren't in the same category. ActiveMQ is ranked #2 in MQ , with an average rating of 8.7, and holds a 20.1% mindshare in the category. Apache Kafka is ranked #3 in SA , with an average rating of 8.7, and holds a 3.8% mindshare. Additionally, 89% of ActiveMQ users are willing to recommend the solution, compared to 96% of Apache Kafka users who would recommend it.

ActiveMQ

Read 28 ActiveMQ reviews

5,809 Views
5,635 Comparison Views

89% willing to recommend

Apache Kafka

Read 92 Apache Kafka reviews

6,471 Views
3,106 Comparison Views

96% willing to recommend

ActiveMQ

Apache Kafka

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Executive Summary

We performed a comparison between ActiveMQ and Apache Kafka based on real PeerSpot user reviews.

Find out what your peers are saying about IBM, Apache, Amazon Web Services (AWS) and others in Message Queue (MQ) Software.

To learn more, read our detailed Message Queue (MQ) Software Report (Updated: July 2026).

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Message Queue (MQ) Software

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

ActiveMQ

Average Rating

8.0

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

Message Queue (MQ) Software (2nd)

Apache Kafka

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Streaming Analytics (3rd)

Mindshare comparison

ActiveMQ and Apache Kafka aren’t in the same category and serve different purposes. ActiveMQ is designed for Message Queue (MQ) Software and holds a mindshare of 20.1%, down 26.2% compared to last year.
Apache Kafka, on the other hand, focuses on Streaming Analytics, holds 3.8% mindshare, up 3.5% since last year.

Message Queue (MQ) Software Mindshare Distribution
Product	Mindshare (%)
ActiveMQ	20.1%
IBM MQ	21.0%
VMware Tanzu Data Solutions	9.7%
Other	49.2%

Message Queue (MQ) Software

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

Streaming Analytics

Featured Reviews

MoumitaDas

Software Engineer III at a financial services firm with 10,001+ employees

Integration capabilities enhance message handling without human interaction

With ActiveMQ there should be more options. If you work with other technologies, for example, Java, there are many options. We can integrate the way we want ActiveMQ. We can create partitions and clusters, but AP is not providing such options currently. It only provides time, request response timing, the number of requests that need to be handled, and protocol types. The configuration needs to be broadened inside AP to perform in a better way. Sometimes issues arise in production with ActiveMQ due to the number of requests. For example, if you have configured one thousand requests at a time and it receives one thousand and one messages at a time, it breaks. The configuration aspect is tricky. When configurations are proper, ActiveMQ almost has zero errors.

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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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Quotes from Members

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

Pros

"The installation was pretty straightforward, and it was also easy setting up HA using an NFS share for hosting the KahaDB."

"The installation was straightforward."

"Depending on the problem, AMQ resolved nearly everything."

"The initial setup is straightforward and only takes a few minutes."

"For reliable messaging, the most valuable feature of ActiveMQ for us is ensuring prompt message delivery."

"One of the most important features of ActiveMQ is the ability to set up a network of brokers, and the ability to forward the message to another broker in the network, where there is a demand for messages from a consumer."

"There is a vibrant community, and it is one of the strongest points of this product. We always get answers to our problems. So, my experience with the community support has been good."

"Loose coupling of components by the use of messaging queues allows for completely separate component life cycles and ownership within the organization."

More ActiveMQ pros

"It has become dead simple to connect different application and services, saving a lot of development hours."

"The great thing about Apache Kafka is that we can seamlessly scale the application and, based on demand, we can add nodes without shutting down the environment."

"With such a large digest, I was genuinely impressed at the process being almost real-time."

"Apache Kafka is effective when dealing with large volumes of data flowing at high speeds, requiring real-time processing."

"The most valuable feature of Apache Kafka is Kafka Connect."

"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."

"The publisher-subscriber pattern and low latency are also essential features that greatly piqued my interest."

"The high availability is valuable. It is robust, and we can rely on it for a huge amount of data."

More Apache Kafka pros

Cons

"Distributed message processing would be a nice addition."

"The included admin web app is not sufficient and we ended up disabling it."

"The clustering for sure needs improvement. When we were using it, the only thing available was an active/passive relationship that had to be maintained via shared file storage. That model includes a single point of failure in that storage medium."

"There are some stability issues."

"The solution can improve the other protocols to equal the AMQ protocol they offer."

"I would rate the stability a five out of ten because sometimes it gets stuck, and we have to restart it. We"

"Needs to focus on a certain facet and be good at it, instead of handling support for most of the available message brokers."

"One potential area would be the complexity of the initial setup."

More ActiveMQ cons

"Lacks elasticity and the ability to scale down."

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

"Data pulling and restart ability need improving."

"Kafka requires non-trivial expertise with DevOps to deploy in production at scale. The organization needs to understand ZooKeeper and Kafka and should consider using additional tools, such as MirrorMaker, so that the organization can survive an availability zone or a region going down."

"The UI used to access Kafka topics can be further improved."

"Observability could be improved."

"I would like to see real-time event-based consumption of messages rather than the traditional way through a loop."

"This product guarantees at-least-once delivery."

More Apache Kafka cons

Pricing and Cost Advice

"We are using the open-source version, so we have not looked at any pricing."

"ActiveMQ is open source, so it is free to use."

"We use the open-source version."

"I think the software is free."

"The tool's pricing is reasonable and competitive compared to other solutions."

"I use open source with standard Apache licensing."

"There are no fees because it is open-source."

"The solution is less expensive than its competitors."

More ActiveMQ pricing and cost advice

"I was using the product's free version."

"Apache Kafka is an open-source solution."

"Running a Kafka cluster can be expensive, especially if you need to scale it up to handle large amounts of data."

"Apache Kafka is an open-source solution."

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

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

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

"The price of Apache Kafka is good."

More Apache Kafka pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

24%

Computer Software Company

Manufacturing Company

Comms Service Provider

Financial Services Firm

17%

Outsourcing Company

12%

Manufacturing Company

10%

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	8
Midsize Enterprise	4
Large Enterprise	17

By reviewers
Company Size	Count
Small Business	33
Midsize Enterprise	20
Large Enterprise	51

Questions from the Community

What needs improvement with ActiveMQ?

Pricing is something to consider with ActiveMQ, though cloud pricing is not costly and depends upon the compute selection. Focusing on AI is essential nowadays. AI capabilities require improvement ...

See all answers

What is your primary use case for ActiveMQ?

In my current organization, I'm only working with ActiveMQ. I previously worked with IBM WebSphere MQ.

See all answers

What advice do you have for others considering ActiveMQ?

We have not deployed ActiveMQ's flexible clustering as that requirement is not present for us. We only use active-passive configuration. On a scale of one to ten, I rate ActiveMQ a ten out of ten.

See all answers

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

Comparisons

IBM MQ vs ActiveMQ

Compared 55% of the time

VMware Tanzu Data Solutions vs ActiveMQ

Compared 6% of the time

Red Hat AMQ vs ActiveMQ

Compared 6% of the time

MuleSoft Anypoint Platform vs ActiveMQ

Compared 5% of the time

Amazon MQ vs ActiveMQ

Compared 1% of the time

More ActiveMQ Competitors

PubSub+ Platform vs Apache Kafka

Compared 12% of the time

Red Hat AMQ vs Apache Kafka

Compared 11% of the time

Databricks vs Apache Kafka

Compared 9% of the time

Azure Stream Analytics vs Apache Kafka

Compared 9% of the time

More Apache Kafka Competitors

Product Reports

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ActiveMQ

August 2026

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Buyer's Guide

Apache Kafka

August 2026

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Also Known As

AMQ

No data available

Overview

ActiveMQ is a messaging broker facilitating microservices communication and event management. It supports message queues, Camel routes, and asynchronous communication, enhancing integration capabilities and scalability with a network of brokers.

ActiveMQ efficiently supports message transfer in IoT applications and third-party systems, acting as a hub for code distribution and data flow management. It integrates well with XML and protocols like MQTT, while its fast messaging, reliable delivery, and efficient setup via Docker cater to diverse messaging needs. Though ActiveMQ is cost-effective, challenges exist with scalability, stability, and administration tools. Enhanced documentation and broader protocol support could resolve these issues, improving administration and initial configurations.

What are the key features of ActiveMQ?

Message Queues: Supports efficient queuing systems for distributing messages.
Camel Routes: Facilitates robust routing mechanisms within applications.
High Availability: Ensures reliable service delivery without interruptions.
Asynchronous Communication: Supports real-time interaction across systems.
XML Integration: Provides flexible communication through XML compatibility.
Protocol Support: Works with protocols like MQTT for versatile messaging.
Brokers Network: Enhances scalability with interconnected broker systems.
Docker Setup: Simplifies deployment processes using containerization.

What benefits should users expect from ActiveMQ?

Reliable Delivery: Guarantees messages are delivered promptly and consistently.
Cost-Effectiveness: Ensures affordability for small-scale applications.
Flexible Integration: Offers adaptable messaging solutions with varied systems.
Ease of Setup: Provides straightforward configuration and deployment processes.

ActiveMQ implementation spans industries from IoT, managing device communications and responses, to middleware solutions for payload consumption. It handles registrations and updates, sometimes being used in demonstrations of message broker concepts. Users often leverage it for its message handling efficiency in industry-specific applications.

Apache

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

Sample Customers

University of Washington, Daugherty Systems, CSC, STG Technologies, Inc.

Uber, Netflix, Activision, Spotify, Slack, Pinterest

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July 2026

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