Amazon MSK vs Apache Flink comparison

Amazon Web Services (AWS) and Apache are both solutions in the Streaming Analytics category. Amazon Web Services (AWS) is ranked #6 with an average rating of 7.4, while Apache is ranked #4 with an average rating of 8.0. Amazon Web Services (AWS) holds a 4.9% mindshare in SA, compared to Apache’s 10.9% mindshare. Additionally, 93% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 95% of Apache users who would recommend it.

Amazon MSK

Read 14 Amazon MSK reviews

2,195 Views
2,151 Comparison Views

93% willing to recommend

Apache Flink

Read 19 Apache Flink reviews

3,771 Views
3,771 Comparison Views

95% willing to recommend

Amazon MSK

Apache Flink

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 17, 2024

Apache Flink and Amazon MSK are competing products in the data streaming and processing category. Apache Flink holds an advantage due to its powerful real-time processing capabilities, while Amazon MSK is favored for its seamless integration with AWS services.

Features: Apache Flink offers real-time data processing, low latency applications, and flexible stateful transformations. Its native capability to handle both batch and streaming data without distinction provides a sophisticated solution for complex data workflows. Amazon MSK integrates well with the existing AWS environment, simplifying Kafka-compatible cluster management, and offering robust managed services. Its features focus on effortless AWS integration and a user-friendly message consumption process.

Room for Improvement: Apache Flink could enhance user documentation and ease of deployment to reduce initial setup complexity. It faces challenges in memory management and scalability under certain high-demand scenarios. Its learning curve for new users requires attention. Amazon MSK could improve by offering more competitive cost structures for smaller workloads, enhancing auto-scaling capabilities, and providing more extensive integration with non-AWS platforms. Additionally, reducing dependency on AWS for feature deployment would increase flexibility.

Ease of Deployment and Customer Service: Amazon MSK benefits from AWS's well-established deployment processes and customer service, making it straightforward for businesses familiar with AWS. It provides seamless guidance that reduces deployment time. Apache Flink requires more technical expertise for deployment, which can lead to longer initial setup times. While flexible in deployment, it demands a greater focus on configuration and provisioning of infrastructure compared to MSK.

Pricing and ROI: Apache Flink's open-source model allows for lower initial costs but may involve increased operational expenses over time. It offers cost-efficiency for businesses able to handle DIY implementations. Amazon MSK presents predictable pricing typical of AWS services, providing a quicker ROI due to its managed services and integration benefits. The solution’s cost-effectiveness is a significant advantage for businesses leveraging a comprehensive AWS infrastructure.

To learn more, read our detailed Amazon MSK vs. Apache Flink Report (Updated: March 2026).

Buyer's Guide

Amazon MSK vs. Apache Flink

March 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

Amazon MSK

Ranking in Streaming Analytics

6th

Average Rating

7.2

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Apache Flink

Ranking in Streaming Analytics

4th

Average Rating

7.8

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of March 2026, in the Streaming Analytics category, the mindshare of Amazon MSK is 4.9%, down from 7.9% compared to the previous year. The mindshare of Apache Flink is 10.9%, down from 12.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Apache Flink	10.9%
Amazon MSK	4.9%
Other	84.2%

Streaming Analytics

Featured Reviews

SYED SHAAZ

Co-Founder & CTO at Photios AI

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.

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Aswini Atibudhi

Distinguished AI Leader at Walmart Global Tech at Walmart

Enables robust real-time data processing but documentation needs refinement

Apache Flink is very powerful, but it can be challenging for beginners because it requires prior experience with similar tools and technologies, such as Kafka and batch processing. It's essential to have a clear foundation; hence, it can be tough for beginners. However, once they grasp the concepts and have examples or references, it becomes easier. Intermediate users who are integrating with Kafka or other sources may find it smoother. After setting up and understanding the concepts, it becomes quite stable and scalable, allowing for customization of jobs. Every software, including Apache Flink, has room for improvement as it evolves. One key area for enhancement is user-friendliness and the developer experience; improving documentation and API specifications is essential, as they can currently be verbose and complex. Debugging and local testing pose challenges for newcomers, particularly when learning about concepts such as time semantics and state handling. Although the APIs exist, they aren't intuitive enough. We also need to simplify operational procedures, such as developing tools and tuning Flink clusters, as these processes can be quite complex. Additionally, implementing one-click rollback for failures and improving state management during dynamic scaling while retaining the last states is vital, as the current large states pose scaling challenges.

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

"Amazon MSK's separation of concerns and ease of creating and deploying new features are highly valuable. It just requires to assign them to the topic, and then anyone who needs to consume these messages can do so directly from Amazon MSK. This separation of concerns makes it very convenient, especially for new feature development, as developers can easily access the messages they need without having to deal with complex server communications or protocol setups."

"MSK has a private network that's an out-of-box feature."

"The solution's technical support was helpful."

"Amazon MSK has contributed positively to our real-time analytics capabilities because Fortis's dashboards have dashboard health that needs to be maintained, user logs that need to be maintained, and usage tracking."

"It is a stable product."

"Amazon MSK has significantly improved our organization by building seamless integration between systems."

"I have Amazon MSK integrated with other AWS services such as S3 and Lambda."

More Amazon MSK pros

"The ease of usage, even for complex tasks, stands out."

"The top feature of Apache Flink is its low latency for fast, real-time data. Another great feature is the real-time indicators and alerts which make a big difference when it comes to data processing and analysis."

"Apache Flink offers a range of powerful configurations and experiences for development teams. Its strength lies in its development experience and capabilities."

"The event processing function is the most useful or the most used function. The filter function and the mapping function are also very useful because we have a lot of data to transform. For example, we store a lot of information about a person, and when we want to retrieve this person's details, we need all the details. In the map function, we can actually map all persons based on their age group. That's why the mapping function is very useful. We can really get a lot of events, and then we keep on doing what we need to do."

"The setup was not too difficult."

"With Flink, it provides out-of-the-box checkpointing and state management. It helps us in that way. When Storm used to restart, sometimes we would lose messages. With Flink, it provides guaranteed message processing, which helped us. It also helped us with maintenance or restarts."

"Apache Flink provides faster and low-cost investment for me; I find it to have low hardware requirements, and it's faster with low code, meaning it's easy to understand for moving the streaming data."

"Apache Flink allows you to reduce latency and process data in real-time, making it ideal for such scenarios."

More Apache Flink pros

Cons

"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."

"One of the reasons why we prefer Kafka is because the support is a little bit difficult to manage with Amazon MSK."

"We need to create connectors in Amazon MSK, but there are no default connectors in AWS for that purpose."

"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 cost of using Amazon MSK is high, which is a significant disadvantage, as the increase in cloud costs by 50% to 60% does not justify the savings."

"In my opinion, there are areas in Amazon MSK that could be improved, particularly in terms of configuration. Initially setting it up and getting it connected was quite challenging. The naming conventions for policies were updated by AWS, and some were undocumented, leading to confusion with outdated materials. It took us weeks of trial and error before discovering new methods through hidden tutorials and official documentation."

"Horizontal scale-out is actually not easy, making it an area where improvements are required."

"The configuration seems a little complex and the documentation on the product is not available."

More Amazon MSK cons

"Apache should provide more examples and sample code related to streaming to help me better adapt and utilize the tool."

"Amazon's CloudFormation templates don't allow for direct deployment in the private subnet."

"In terms of improvement, there should be better reporting. You can integrate with reporting solutions but Flink doesn't offer it themselves."

"The solution could be more user-friendly."

"There are more libraries that are missing and also maybe more capabilities for machine learning."

"We have a machine learning team that works with Python, but Apache Flink does not have full support for the language."

"The technical support from Apache is not good; support needs to be improved. I would rate them from one to ten as not good."

"The state maintains checkpoints and they use RocksDB or S3. They are good but sometimes the performance is affected when you use RocksDB for checkpointing."

More Apache Flink cons

Pricing and Cost Advice

"The price of Amazon MSK is less than some competitor solutions, such as Confluence."

"When you create a complete enterprise-driven architecture that is deployable on an enterprise scale, I would say that the prices of Amazon MSK and Confluent Platform become comparable."

"The platform has better pricing than one of its competitors."

"It's an open-source solution."

"It's an open source."

"Apache Flink is open source so we pay no licensing for the use of the software."

"This is an open-source platform that can be used free of charge."

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

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Top Industries

By visitors reading reviews

Financial Services Firm

21%

Computer Software Company

12%

Manufacturing Company

Retailer

Financial Services Firm

19%

Retailer

13%

Computer Software Company

10%

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	7
Large Enterprise	4

By reviewers
Company Size	Count
Small Business	5
Midsize Enterprise	3
Large Enterprise	12

Questions from the Community

What needs improvement with Amazon MSK?

See all answers

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 ...

See all answers

What advice do you have for others considering Amazon MSK?

We are working with Amazon MSK product, Managed Streaming for Apache Kafka. The main benefits I have seen from using Amazon MSK is that as a B2B enterprise client, we have many SLAs to fulfill. Tra...

See all answers

What is your experience regarding pricing and costs for Apache Flink?

The solution is expensive. I rate the product’s pricing a nine out of ten, where one is cheap and ten is expensive.

See all answers

What needs improvement with Apache Flink?

Apache could improve Apache Flink by providing more functionality, as they need to fully support data integration. The connectors are still very few for Apache Flink. There is a lack of functionali...

See all answers

What is your primary use case for Apache Flink?

I am working with Apache Flink, which is the tool we use for data integration. Apache Flink is for data, and we are working on the data integration project, not big data, using Apache Flink and Apa...

See all answers

Comparisons

Azure Stream Analytics vs Amazon MSK

Compared 18% of the time

Confluent vs Amazon MSK

Compared 11% of the time

Aiven Platform vs Amazon MSK

Compared 9% of the time

Amazon Kinesis vs Amazon MSK

Compared 9% of the time

Oracle Stream Analytics vs Amazon MSK

Compared 6% of the time

More Amazon MSK Competitors

Spring Cloud Data Flow vs Apache Flink

Compared 11% of the time

Databricks vs Apache Flink

Compared 9% of the time

Confluent vs Apache Flink

Compared 9% of the time

Amazon Kinesis vs Apache Flink

Compared 9% of the time

PubSub+ Platform vs Apache Flink

Compared 5% of the time

More Apache Flink Competitors

Product Reports

Buyer's Guide

Amazon MSK

March 2026

Download Amazon MSK product report

Buyer's Guide

Apache Flink

March 2026

Download Apache Flink product report

Also Known As

Amazon Managed Streaming for Apache Kafka

Flink

Overview

Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that enables you to build and run applications that use Apache Kafka to process streaming data. Amazon MSK provides the control-plane operations, such as those for creating, updating, and deleting clusters.

Amazon Web Services (AWS)

Apache Flink is an open-source batch and stream data processing engine. It can be used for batch, micro-batch, and real-time processing. Flink is a programming model that combines the benefits of batch processing and streaming analytics by providing a unified programming interface for both data sources, allowing users to write programs that seamlessly switch between the two modes. It can also be used for interactive queries.

Flink can be used as an alternative to MapReduce for executing iterative algorithms on large datasets in parallel. It was developed specifically for large to extremely large data sets that require complex iterative algorithms.

Flink is a fast and reliable framework developed in Java, Scala, and Python. It runs on the cluster that consists of data nodes and managers. It has a rich set of features that can be used out of the box in order to build sophisticated applications.

Flink has a robust API and is ready to be used with Hadoop, Cassandra, Hive, Impala, Kafka, MySQL/MariaDB, Neo4j, as well as any other NoSQL database.

Apache Flink Features

Distributed execution of streaming programs on clusters of computers
Support for multiple data sources and sinks: this includes Hadoop file systems, databases, and other data sources
Streaming SQL query engine with support for windowing functions
Low latency query execution in milliseconds
Runs in a distributed fashion: it can be deployed on multiple machines or nodes to increase performance and reliability of data processing pipelines.
Powerful API that supports both batch and streaming applications
Runs on clusters of commodity hardware with minimal configuration
Can be integrated with other technologies, such as Apache Spark for complex data mining

Apache Flink Benefits

Ease of use: Flink has an intuitive API and provides high-level abstractions for handling data streams. Even beginners in the field can work with the platform with ease.

Fault tolerance: Flink can automatically detect and recover from failures in the system.

Scalability: Flink scales to thousands of nodes. It can run on clusters of any size and the user does not have to worry about managing the cluster.

Reviews from Real Users

Apache Flink stands out among its competitors for a number of reasons. Two major ones are its low latency and its user-friendly interface. PeerSpot users take note of the advantages of these features in their reviews:

The head of data and analytics at a computer software company notes, “The top feature of Apache Flink is its low latency for fast, real-time data. Another great feature is the real-time indicators and alerts which make a big difference when it comes to data processing and analysis.”

Ertugrul A., manager at a computer software company, writes, “It's usable and affordable. It is user-friendly and the reporting is good.”

Apache

Sample Customers

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers

LogRhythm, Inc., Inter-American Development Bank, Scientific Technologies Corporation, LotLinx, Inc., Benevity, Inc.

Buyer's Guide

Amazon MSK vs. Apache Flink

March 2026

Free Report: Amazon MSK vs. Apache Flink

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