Amazon MSK vs Apache Flink comparison

Why PeerSpot?

Amazon Web Services (AWS) and Apache are both solutions in the Streaming Analytics category. Amazon Web Services (AWS) is ranked #14 with an average rating of 7.0, while Apache is ranked #4 with an average rating of 8.0. Amazon Web Services (AWS) holds a 3.9% mindshare in SA, compared to Apache’s 7.0% 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

2,770 Views
2,715 Comparison Views

93% willing to recommend

Apache Flink

Read 19 Apache Flink reviews

5,102 Views
5,102 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: September 2026).

Buyer's Guide

Amazon MSK vs. Apache Flink

September 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

14th

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 September 2026, in the Streaming Analytics category, the mindshare of Amazon MSK is 3.9%, down from 6.0% compared to the previous year. The mindshare of Apache Flink is 7.0%, down from 14.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Apache Flink	7.0%
Amazon MSK	3.9%
Other	89.1%

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.

Read full review

Sanjay Srivastava

Software Architect at IBM

Streaming workflows have improved data integration and support real-time pipelines across platforms

We are not using Apache Flink in its advanced window capabilities. We are using the Apache Flink job in Apache SeaTunnel, meaning we can write the code inside Apache SeaTunnel. Currently, we are moving; both solutions are there. We are doing it on-premises with the help of Kubernetes and OpenShift. The main reason why Apache Flink is better is that it has more functions, and being open source with easy code in Apache SeaTunnel helps us achieve that. Cost is a major issue. I would rate the stability of the product as an eight. For Apache Flink, the final point can be rated an eight. I can recommend Apache Flink to other users for streaming support, and I am recommending it. I would rate this review an eight overall.

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

"It offers good stability."

"The scalability and usability are quite remarkable."

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

"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."

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

"The most valuable feature of Amazon MSK is the integration."

"Amazon MSK's scalability is very good."

More Amazon MSK pros

"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."

"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."

"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 main advantage is the turnaround time, which has been reduced drastically because of Apache Flink, and now everything is in almost real time with no waiting or lag of data in the application while machine resources are utilized much more efficiently."

"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."

"The end-to-end latency was drastically reduced, and our capability of handling high throughput has increased by using Flink."

"We value this solution's intricate system because it comes with a state inside the mechanism and product, allowing us to process batch data, stream to real-time and build pipelines, and we do not need to process data from the beginning when we pause as we can continue from the same point where we stopped, helping us save time as 95% of our pipelines will now be on Amazon and we'll save money by saving time."

More Apache Flink pros

Cons

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

"MSK should be easier to integrate with other solutions. It should be more flexible, integration-wise."

"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."

"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."

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

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

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

"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."

More Amazon MSK cons

"One way to improve Flink would be to enhance integration between different ecosystems."

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

"In a future release, they could improve on making the error descriptions more clear."

"Apache Flink should improve its data capability and data migration."

"Flink has become a lot more stable but the machine learning library is still not very flexible."

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

"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."

"In terms of stability with Flink, it is something that you have to deal with every time. Stability is the number one problem that we have seen with Flink, and it really depends on the kind of problem that you're trying to solve."

More Apache Flink cons

Pricing and Cost Advice

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

"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."

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

"It's an open source."

"It's an open-source solution."

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

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

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

Manufacturing Company

10%

Comms Service Provider

Construction Company

Financial Services Firm

17%

Retailer

14%

Computer Software Company

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	5

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 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

What advice do you have for others considering Apache Flink?

See all answers

Comparisons

Azure Stream Analytics vs Amazon MSK

Compared 13% of the time

Confluent vs Amazon MSK

Compared 9% of the time

Aiven Platform vs Amazon MSK

Compared 9% of the time

Amazon Kinesis vs Amazon MSK

Compared 9% of the time

PubSub+ Platform vs Amazon MSK

Compared 5% of the time

More Amazon MSK Competitors

Azure Stream Analytics vs Apache Flink

Compared 8% of the time

Spring Cloud Data Flow vs Apache Flink

Compared 8% of the time

Amazon Kinesis vs Apache Flink

Compared 7% of the time

Google Cloud Dataflow vs Apache Flink

Compared 6% of the time

More Apache Flink Competitors

Product Reports

Buyer's Guide

Amazon MSK

September 2026

Download Amazon MSK product report

Buyer's Guide

Apache Flink

September 2026

Download Apache Flink product report

Also Known As

Amazon Managed Streaming for Apache Kafka

Flink

Overview

Amazon MSK offers seamless AWS integration, simplifying development and operation. It supports efficient data streaming and ensures cost-effective scalability without additional setup needs.

Amazon MSK stands out for its effortless creation, deployment, and access to new features without complex VPC configurations. Automating scalability, it demands minimal intervention, making it ideal for high-volume workflows. Developers benefit from real-time analytics, event sourcing, and log ingestion, aiding in dashboard maintenance and user log tracking. However, integration challenges exist as some face inflexibility, intricate configurations, and plugin development difficulties. Schema validation, connector variety, and complex update processes lead some to seek alternatives. Noteworthy for order data streaming, transaction tracking in retail and banking, and other real-time data applications, Amazon MSK remains attractive despite high cost concerns.

What are Amazon MSK's key features?

Seamless AWS Integration: No additional setup or VPC needed.
Automatic Scalability: Minimal intervention thanks to automatic configurations.
Real-time Analytics: Supports event sourcing and log ingestion.
Cost-effective: Tailored for high-volume workflows.
Encryption: Secure data during migrations.

What benefits should users consider when evaluating Amazon MSK?

Efficiency: Effortless deployment and development support.
Scalability: Automated processes reduce operational overhead.
Cost Management: Financially viable for larger data volumes.
Security: High level of encryption during data transfers.
Data Handling: Effective for streaming, integration, and real-time processing.

In retail and banking, Amazon MSK facilitates order data streaming and transaction tracking. Its capabilities in supporting CDC pipelines, high-volume data management, and asynchronous processes make it favorable for integrating systems, streaming IoT data, and managing dashboard flows. Challenges in integration and configuration persist, nudging users to explore different options in certain contexts.

Amazon Web Services (AWS)

Apache Flink is a powerful open-source framework for stateful computations over data streams, designed for both real-time and batch processing. It efficiently handles massive volumes of data with low-latency responses, offering versatility for complex event processing scenarios.

Apache Flink excels in processing high-throughput data streams, enabling seamless state management across distributed applications. Users appreciate its robust features like stateful transformations and checkpointing, simplifying deployment in diverse environments. Though powerful, it poses challenges for beginners due to its complexity and limited documentation, requiring some prior experience to master. Its flexible integration with systems like Kafka and support for Kubernetes on AWS makes it suitable for demanding environments where quick, real-time analysis is essential.

What are the key features of Apache Flink?

Stateful Transformations: Allows complex stateful operations on data streams with precise handling.
Low Latency: Ensures real-time data processing with minimal delays.
Checkpointing: Provides efficient and reliable checkpointing for fault tolerance.
Kafka Integration: Easy integration with Kafka for seamless data ingestion and processing.
API Support: Provides robust APIs for diverse data processing needs.
Flexible Deployment: Offers options for deploying on-premise or in cloud environments.

What benefits should users look for?

Versatility: Supports both batch and stream processing in a unified model.
Community Support: Backed by an active community that continuously enhances its features.
Ease of Use: Simplifies the coding process compared to similar frameworks like Apache Storm.
Real-Time Analytics: Facilitates immediate insights and data-driven decision-making.

Organizations leverage Apache Flink primarily for real-time data processing in sectors such as retail, transportation, and telecommunications. By deploying on AWS with Kubernetes, companies can utilize it for data cleaning, generating customer insights, and providing swift real-time updates. It effectively manages millions of events per second, serving use cases like cab aggregations, map-making, and outlier detection in telecom networks, enabling seamless integration of streaming data with existing pipelines.

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 2026

Free Report: Amazon MSK vs. Apache Flink

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