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 7.2, while Apache is ranked #5 with an average rating of 7.8. Amazon Web Services (AWS) holds a 5.9% mindshare in SA, compared to Apache’s 14.8% mindshare. Additionally, 93% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 94% of Apache users who would recommend it.

Amazon MSK

Read 14 Amazon MSK reviews

2,530 Views
2,479 Comparison Views

93% willing to recommend

Apache Flink

Read 18 Apache Flink reviews

3,815 Views
3,815 Comparison Views

94% 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: September 2025).

Buyer's Guide

Amazon MSK vs. Apache Flink

September 2025

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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

5th

Average Rating

7.8

Reviews Sentiment

6.9

Number of Reviews

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 Flink is 14.8%, up from 10.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Market Share Distribution
Product	Market Share (%)
Apache Flink	14.8%
Amazon MSK	5.9%
Other	79.3%

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.

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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

"It provides installations, scaling, and other functionalities straight out of the box."

"What I appreciate most about Amazon MSK is that it doesn't require extensive concern about the configurations; it starts checking how the brokers are functioning, and automatically, Amazon MSK tries to resolve all the problems."

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

"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."

"The solution's technical support was helpful."

"It is a stable product."

"Overall, it is very cost-effective based on the workflow."

"The scalability and usability are quite remarkable."

More Amazon MSK pros

"The setup was not too difficult."

"It provides us the flexibility to deploy it on any cluster without being constrained by cloud-based limitations."

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

"What I appreciate best about Apache Flink is that it's open source and geared towards a distributed stream processing framework."

"It is user-friendly and the reporting is good."

"Another feature is how Flink handles its radiuses. It has something called the checkpointing concept. You're dealing with billions and billions of requests, so your system is going to fail in large storage systems. Flink handles this by using the concept of checkpointing and savepointing, where they write the aggregated state into some separate storage. So in case of failure, you can basically recall from that state and come back."

"Allows us to process batch data, stream to real-time and build pipelines."

"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."

More Apache Flink pros

Cons

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

"It should be more flexible, integration-wise."

"The downside of Amazon MSK is that when I needed to make a small change in the MSK configuration, it wasn't possible. I had to remove and drop all the clusters and recreate them again, which is complicated in a production environment."

"The product's schema support needs enhancement. It will help enhance integration with many kinds of languages of programming languages, especially for environments using languages like .NET."

"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."

"Amazon MSK could improve on the features they offer. They are still lagging behind Confluence."

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

"It would be really helpful if Amazon MSK could provide a single installation that covers all the servers."

More Amazon MSK cons

"PyFlink is not as fully featured as Python itself, so there are some limitations to what you can do with it."

"Apache Flink's documentation should be available in more languages."

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

"There is room for improvement in the initial setup process."

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

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

"There is a learning curve. It takes time to learn."

"One way to improve Flink would be to enhance integration between different ecosystems. For example, there could be more integration with other big data vendors and platforms similar in scope to how Apache Flink works with Cloudera. Apache Flink is a part of the same ecosystem as Cloudera, and for batch processing it's actually very useful but for real-time processing there could be more development with regards to the big data capabilities amongst the various ecosystems out there."

More Apache Flink cons

Pricing and Cost Advice

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

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

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

"It's an open-source solution."

"It's an open source."

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

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

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Top Industries

By visitors reading reviews

Financial Services Firm

23%

Computer Software Company

14%

Manufacturing Company

Comms Service Provider

Financial Services Firm

22%

Retailer

11%

Computer Software Company

11%

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	11

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.

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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 ...

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What do you like most about Apache Flink?

The product helps us to create both simple and complex data processing tasks. Over time, it has facilitated integration and navigation across multiple data sources tailored to each client's needs. ...

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 should provide more examples and sample code related to streaming to help me better adapt and utilize the tool. There is a need for increased awareness and education, especially around best ...

See all answers

Comparisons

Azure Stream Analytics vs Amazon MSK

Compared 34% of the time

Confluent vs Amazon MSK

Compared 16% of the time

Amazon Kinesis vs Amazon MSK

Compared 7% of the time

Apache Pulsar vs Amazon MSK

Compared 7% of the time

Google Cloud Dataflow vs Amazon MSK

Compared 5% of the time

More Amazon MSK Competitors

Spring Cloud Data Flow vs Apache Flink

Compared 20% of the time

Databricks vs Apache Flink

Compared 14% of the time

Amazon Kinesis vs Apache Flink

Compared 10% of the time

Confluent vs Apache Flink

Compared 9% of the time

Apache Pulsar vs Apache Flink

Compared 5% of the time

More Apache Flink Competitors

Product Reports

Buyer's Guide

Amazon MSK

September 2025

Download Amazon MSK product report

Buyer's Guide

Apache Flink

September 2025

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

September 2025

Free Report: Amazon MSK vs. Apache Flink

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