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Amazon MQ vs Apache Kafka comparison

 

Comparison Buyer's Guide

Executive Summary

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

Amazon MQ
Average Rating
8.4
Reviews Sentiment
5.9
Number of Reviews
8
Ranking in other categories
Message Queue (MQ) Software (7th)
Apache Kafka
Average Rating
8.2
Reviews Sentiment
6.8
Number of Reviews
92
Ranking in other categories
Streaming Analytics (3rd)
 

Mindshare comparison

Amazon MQ and Apache Kafka aren’t in the same category and serve different purposes. Amazon MQ is designed for Message Queue (MQ) Software and holds a mindshare of 3.9%, up 3.5% compared to last year.
Apache Kafka, on the other hand, focuses on Streaming Analytics, holds 3.9% mindshare, up 3.0% since last year.
Message Queue (MQ) Software Mindshare Distribution
ProductMindshare (%)
Amazon MQ3.9%
IBM MQ20.7%
ActiveMQ19.8%
Other55.6%
Message Queue (MQ) Software
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Apache Kafka3.9%
Apache Flink8.2%
Databricks7.9%
Other80.0%
Streaming Analytics
 

Featured Reviews

RamilCerrada - PeerSpot reviewer
Solution architect at SM Supermalls
Has provided consistent functionality across on-premise and cloud while simplifying cloud integration
I have experience with on-premise setups using ActiveMQ and RabbitMQ, but with regards to AWS, I use it via cloud only. There's a free tier with Amazon MQ based on their website, which is a six-month free trial of a single instance, allowing per month usage of either ActiveMQ or RabbitMQ, five gig of Amazon EFS storage, and for ActiveMQ, it's 20 gig of Amazon EBS storage for RabbitMQ. I did not purchase Amazon MQ through AWS Marketplace. Amazon MQ has published information about having 650 hours of free trial usage. This can be found via the AWS website by searching for AWS MQ. On a scale of one to ten, I rate Amazon MQ an eight out of ten.
Varuns Ug - PeerSpot reviewer
Senior Software Developer at NIT
Event-driven workflows have improved payment processing and reduced latency across services
One area for improvement in Apache Kafka is operational complexity. Running and maintaining an Apache Kafka cluster at scale involves handling partitions, replications, retention policies, rebalancing, and monitoring, which requires strong expertise. Debugging and observability can be complex in large systems, as troubleshooting issues such as consumer lag, offset management problems, or uneven partition distribution can become challenging. The learning curve is relatively steep, requiring a good understanding of concepts such as partition, consumer group, offset commit, and delivery guarantees to avoid subtle production issues. One area where Apache Kafka could improve is the developer experience around debugging and tracing events end to end. In distributed systems, when an event passes through multiple topics and consumer services, troubleshooting can become time-consuming. Better built-in observability for tracing event flows across services would be very useful.

Quotes from Members

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

Pros

"The tool's most valuable feature is its managed service aspect. It's simple to implement and use. It requires minimal effort to maintain business operations."
"Amazon MQ is important for being collaborative, allowing for centralized information."
"Amazon MQ is a secure solution."
"We have found Amazon MQ to provide scalability, robustness, and security."
"Amazon MQ is a very scalable solution."
"Since we utilize AWS, it's easy to integrate Amazon MQ and work with other third-party software, as they have standard communications via API or native language."
"The initial Amazon MQ setup is very easy both when you do it on your own or use the self-managed instance."
"Amazon MQ is managed by AWS and is easy to use."
"We have definitely seen a return on investment from Apache Kafka, and I can say we have noticed a strong return on investment largely due to improved scalability and reduced operational friction in asynchronous workflows, saving time and effectively handling traffic spikes."
"The open-source version is relatively straightforward to set up and only takes a few minutes."
"When we're working with big data, we need a throughput computing panel, which is something that Kafka provides, and something we find extremely valuable."
"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."
"It seemed pretty stable and didn't have any issues at all."
"The connectors provided by the solution are valuable."
"Resiliency is great and also the fact that it handles different data formats."
"All the features of Apache Kafka are valuable, I cannot single out one feature."
 

Cons

"Amazon MQ is a good solution for small and medium-sized enterprises. It's open-source software, which means it's cheaper than its competitors."
"Monitoring capabilities are not yet fully developed, since it's a message broker service, so it focuses more on the health of Apache."
"On a scale of one to 10, one being the best and 10 being the worst, I would give Amazon MQ an eight for overall performance."
"The solution needs improvement in the back end and security."
"Amazon MQ isn't a cheap tool."
"In community support, especially with distributed systems and integration, there is a need for better system organization."
"Depending on your use cases, Amazon MQ can be cheap or expensive."
"The product should improve its monitoring capabilities. It needs to improve the pricing also."
"More adapters for connecting to different systems need to be available."
"The standard Kafka Java library, which is shipped with the product, is too complex for inexperienced users."
"The solution could always add a few more features to enhance its usage."
"An area for improvement would be growth."
"would like to see real-time event-based consumption of messages rather than the traditional way through a loop. The traditional messaging system works by listing and looping with a small wait to check to see what the messages are. A push system is where you have something that is ready to receive a message and when the message comes in and hits the partition, it goes straight to the consumer versus the consumer having to pull. I believe this consumer approach is something they are working on and may come in an upcoming release. However, that is message consumption versus message listening."
"Kafka 2.0 has been released for over a month, and I wanted to try out the new features. However, the configuration is a little bit complicated: Kafka Broker, Kafka Manager, ZooKeeper Servers, etc."
"Kafka can allow for duplicates, which isn't as helpful in some of our scenarios."
"Config management can be better. We are always trying to find the best configs, which is a challenge."
 

Pricing and Cost Advice

"As a client or as an end user, I would say that Google Cloud Storage or Google Cloud are cheaper than Amazon MQ."
"Depending on your use cases, Amazon MQ can be cheap or expensive."
"I was using the product's free version."
"Kafka is open-source and it is cheaper than any other product."
"Kafka is more reasonably priced than IBM MQ."
"Apache Kafka is free."
"Apache Kafka is open-source and can be used free of charge."
"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."
"It is approximately $600,000 USD."
"Apache Kafka has an open-source pricing."
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Top Industries

By visitors reading reviews
Financial Services Firm
20%
Comms Service Provider
13%
Manufacturing Company
9%
Government
6%
Financial Services Firm
18%
Manufacturing Company
10%
Computer Software Company
9%
Outsourcing Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business2
Midsize Enterprise3
Large Enterprise3
By reviewers
Company SizeCount
Small Business32
Midsize Enterprise20
Large Enterprise51
 

Questions from the Community

What needs improvement with Amazon MQ?
Amazon MQ needs to have data collected on performance to analyze trends for improvement. Additionally, some tools can suggest how to improve performance in terms of speed, time, and processing, whi...
What is your primary use case for Amazon MQ?
I have some experience working with Amazon MQ.
What advice do you have for others considering Amazon MQ?
I have experience with on-premise setups using ActiveMQ and RabbitMQ, but with regards to AWS, I use it via cloud only. There's a free tier with Amazon MQ based on their website, which is a six-mon...
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...
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.
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...
 

Comparisons

 

Overview

 

Sample Customers

SkipTheDishes, Malmberg, Dealer.com, Bench Accounting
Uber, Netflix, Activision, Spotify, Slack, Pinterest
Find out what your peers are saying about IBM, Apache, Amazon Web Services (AWS) and others in Message Queue (MQ) Software. Updated: June 2026.
900,644 professionals have used our research since 2012.