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Amazon MSK vs Apache Kafka on Confluent Cloud 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:
 

ROI

Sentiment score
4.1
Amazon MSK saves time and money, promotes innovation with flexible pricing, yet some users find costs hard to justify.
Sentiment score
3.1
Apache Kafka on Confluent Cloud boosts ROI and reliability, but adoption may be challenging due to associated costs.
Returns depend on the application you deploy and the amount of benefits you are getting, which depends on how many applications you are deploying, what are the sorts of applications, and what are the requirements.
 

Customer Service

Sentiment score
6.2
Amazon MSK support varies; some praise its effectiveness, while others note average service and seek external assistance.
Sentiment score
4.3
Apache Kafka's Confluent Cloud support is well-rated, effective with tools, timely, despite minor communication issues and preference for forums.
They can manage most of our queries, and for what they cannot manage, they guide us through the process of finding out.
Amazon's support is excellent.
I would rate them eight if 10 was the best and one was the worst.
 

Scalability Issues

Sentiment score
6.0
Amazon MSK is viewed as scalable, manageable, appealing to various environments, but may require manual scaling adjustments.
Sentiment score
3.8
Apache Kafka on Confluent Cloud is praised for scalability, despite some reliability issues, with managed services reducing operational burdens.
The functionality for scaling comes out of the box and is very effective.
As a B2B enterprise client, our clientele consists of large ticket clients but low amounts of users.
 

Stability Issues

Sentiment score
7.3
Amazon MSK is stable with high ratings; minor issues are unrelated to MSK, maintaining success rates of 91% under load.
Sentiment score
3.5
Users consider Apache Kafka on Confluent Cloud stable but report performance drops with traffic spikes and dashboard management challenges.
It doesn't require any maintenance on my end yet, as I haven't had any issues.
 

Room For Improvement

Amazon MSK struggles with integration, configuration complexities, high costs, and operational challenges compared to services like Kinesis.
Confluent Cloud improves Kafka integration with PyTRAN and Microsoft, but faces challenges in real-time processing, monitoring, and cost.
There are preset configurations and limited configurations that we can set for our unique use case.
The increase in cloud costs by 50% to 60% does not justify the savings.
I had to remove and drop all the clusters and recreate them again, which is complicated in a production environment.
If it were easier to configure clusters and had more straightforward configuration, high-level API abstraction in the APIs could improve it.
Observability and monitoring are areas that could be enhanced.
 

Setup Cost

Amazon MSK is competitively priced with variable costs, appealing to enterprise users but potentially expensive for some.
Enterprise users see Apache Kafka on Confluent Cloud's pricing as flexible but requiring careful management for cost optimization.
Once we started using Kafka, our cloud costs rose by 50% to 60%.
We use Kafka M5 Large instance, and depending on the instances, that is the cost we have, along with storage cost and data transfer costs.
 

Valuable Features

Amazon MSK integrates AWS services, offering cost-effective, automated scaling, ease of use, real-time analytics, encryption, and event sourcing.
Apache Kafka on Confluent Cloud offers scalable streaming, seamless integration, and efficient data processing, simplifying microservices and multi-cloud support.
The ability to handle everything, including installation, with minimal human intervention, is a strong point.
It starts checking how the brokers are functioning, and automatically, Amazon MSK tries to resolve all the problems.
The best features of Amazon MSK are the real-time analytics that are excellent.
These features are important due to scalability and resiliency.
The Kafka Streams API helps with real-time data transformations and aggregations.
 

Categories and Ranking

Amazon MSK
Ranking in Streaming Analytics
6th
Average Rating
7.2
Reviews Sentiment
6.5
Number of Reviews
14
Ranking in other categories
No ranking in other categories
Apache Kafka on Confluent C...
Ranking in Streaming Analytics
11th
Average Rating
8.6
Reviews Sentiment
3.7
Number of Reviews
14
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of October 2025, in the Streaming Analytics category, the mindshare of Amazon MSK is 5.9%, down from 9.1% compared to the previous year. The mindshare of Apache Kafka on Confluent Cloud is 0.1%, up from 0.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Amazon MSK5.9%
Apache Kafka on Confluent Cloud0.1%
Other94.0%
Streaming Analytics
 

Featured Reviews

SYED SHAAZ - PeerSpot reviewer
Improved data streaming and integration challenges prompt search for alternatives
The integration capabilities of Amazon MSK are not very flexible. If you have your own self-managed Kafka, that helps significantly because you can set up configurations. We are considering self-managed Kafka since our product is only one year old. The Kafka integrations are fine, but the configurations are an issue. The only issue with Amazon MSK that we are facing is the configurations. There are preset configurations and limited configurations that we can set for our unique use case. The product could improve by allowing us to set different configurations. I would also like to see Amazon MSK improve in the area of connectors. We are considering Confluent Cloud because they have many more connectors. They have KSQL DB and governance features. It is slightly costlier, but Confluent offers more flexibility with their connectors.
FABIO LUIS VELLOSO DA SILVA - PeerSpot reviewer
Has enabled asynchronous communication and real-time data processing with strong performance
The valuable features with Apache Kafka on Confluent Cloud are the messaging and the asynchronous messages; it's the basic, not advanced usage. It's only to create clusters to receive and send messages. The point is the asynchronous messages and the scalability; it is important for us. To guarantee the compliance of the architecture and the patterns for the company, to provide scalability, and to guarantee the security to send the messages. The Kafka Streams API helps with real-time data transformations and aggregations. It's very fast and helps us to create the project, guarantee the message delivery, and the performance. It's a good experience with very impressive processing and a very impressive project and product.
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Top Industries

By visitors reading reviews
Financial Services Firm
23%
Computer Software Company
14%
Manufacturing Company
6%
Comms Service Provider
5%
Financial Services Firm
13%
Manufacturing Company
7%
Educational Organization
6%
Government
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise7
Large Enterprise4
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise3
Large Enterprise6
 

Questions from the Community

What do you like most about Amazon MSK?
Amazon MSK has significantly improved our organization by building seamless integration between systems.
What needs improvement with Amazon MSK?
The integration capabilities of Amazon MSK are not very flexible. If you have your own self-managed Kafka, that helps significantly because you can set up configurations. We are considering self-ma...
What is your primary use case for Amazon MSK?
We are recently working with Amazon MSK at Fortis, where we have multiple dashboards in our revenue intelligence platform. We are streaming data from different apps into those dashboards. The data ...
What do you like most about Apache Kafka on Confluent Cloud?
Kafka and Confluent Cloud have proven to be cost-effective, especially when compared to other tools. In a recent BI integration program over the past year, we assessed multiple use cases spanning s...
What needs improvement with Apache Kafka on Confluent Cloud?
If it were easier to configure clusters and had more straightforward configuration, high-level API abstraction in the APIs could improve it. The clustering is a little hard for juniors and clients....
What is your primary use case for Apache Kafka on Confluent Cloud?
We need to send a lot of asynchronous messages in this project, and we use the middleware and Apache Kafka on Confluent Cloud to guarantee asynchronous messaging between the services. We use Apache...
 

Also Known As

Amazon Managed Streaming for Apache Kafka
No data available
 

Overview

 

Sample Customers

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
Information Not Available
Find out what your peers are saying about Amazon MSK vs. Apache Kafka on Confluent Cloud and other solutions. Updated: September 2025.
869,202 professionals have used our research since 2012.