Amazon MSK vs Spring Cloud Data Flow comparison

Amazon Web Services (AWS) and Broadcom are both solutions in the Streaming Analytics category. Amazon Web Services (AWS) is ranked #6 with an average rating of 7.2, while Broadcom is ranked #10 with an average rating of 7.8. Amazon Web Services (AWS) holds a 5.2% mindshare in SA, compared to Broadcom’s 4.5% mindshare. Additionally, 93% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 88% of Broadcom users who would recommend it.

Amazon MSK

Read 14 Amazon MSK reviews

2,291 Views
2,245 Comparison Views

93% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

3,005 Views
1,322 Comparison Views

88% willing to recommend

Amazon MSK

Spring Cloud Data Flow

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 17, 2024

Spring Cloud Data Flow and Amazon MSK focus on different aspects of real-time data processing. While Spring Cloud Data Flow has competitive pricing and deployment flexibility, Amazon MSK offers a wider range of integrations, making it more appealing for large-scale deployments.

Features: Spring Cloud Data Flow stands out for its flexible data flow orchestration and support for various programming languages. It effectively uses Spring components for microservices management and offers a simple programming model with auto-configuration. Amazon MSK provides seamless Apache Kafka cluster management, robust AWS integration, and features like high throughput and low latency, making it suitable for extensive data ecosystems.

Room for Improvement: Spring Cloud Data Flow could enhance its graphical environment for data visualization and offer more off-the-shelf components for easier implementation. Improvements in custom component development and a more intuitive interface would benefit users. Amazon MSK might expand features for non-AWS services, improve cost efficiency for smaller workloads, and simplify the setup for complex server communications.

Ease of Deployment and Customer Service: Spring Cloud Data Flow offers rapid deployment across various environments and has strong community support with detailed documentation. Amazon MSK excels at reducing operational complexity with its managed Kafka service and benefits from AWS's reliable customer support, providing effective problem resolution.

Pricing and ROI: Spring Cloud Data Flow leverages open-source technologies for cost-effective scaling, appealing to budget-conscious projects with promising ROI. Amazon MSK may have higher costs, but its streamlined operations and AWS integration justify the investment for businesses prioritizing scalability and comprehensive features.

To learn more, read our detailed Amazon MSK vs. Spring Cloud Data Flow Report (Updated: December 2025).

Buyer's Guide

Amazon MSK vs. Spring Cloud Data Flow

December 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

Spring Cloud Data Flow

Ranking in Streaming Analytics

10th

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Integration (21st)

Mindshare comparison

As of December 2025, in the Streaming Analytics category, the mindshare of Amazon MSK is 5.2%, down from 8.5% compared to the previous year. The mindshare of Spring Cloud Data Flow is 4.5%, down from 4.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Market Share Distribution
Product	Market Share (%)
Amazon MSK	5.2%
Spring Cloud Data Flow	4.5%
Other	90.3%

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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Lipika Naik

Senior Software Engineer at QBE Regional Insurance

Provides ease of integration with other cloud platforms

Spring Cloud Data Flow is a useful product if I consider how there are different providers with whom my company had to deal, and most of them offer cloud-based products. I can't explain any crucial circumstances where the product's integration capabilities were helpful, but the aforementioned details explain the scenario for which I used the solution. I was only involved with the development of the product and not with the data pipeline configuration phase. The use of Spring Cloud Data Flow greatly impacted projects' time to market since our company's intention was to actually deploy and ensure that the payment platform integrated with it, which was an easy process. The product's user interface was very intuitive. The tool was deployed in multiple environments, but I am not sure about the production. From the time I started taking up the job in my current organization, I saw that we have deployed the tool in multiple environments wherein the number of users extensively used the product in the UAT environment, which is one of the most stable environments. There were 20 different methods to test the tool. I wouldn't be able to tell you the production details of the tool as I was more part of the production deployment, but I can say that it was deployed with the intent of making it available for 10,000 users. Those who plan to use the product should enjoy the flexibility of the solution. I rate the tool a nine out of ten.

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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

"Amazon MSK's scalability is very good."

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

"It offers good stability."

"The scalability and usability are quite remarkable."

"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."

"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."

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

More Amazon MSK pros

"There are a lot of options in Spring Cloud. It's flexible in terms of how we can use it. It's a full infrastructure."

"The best thing I like about Spring Cloud Data Flow is its plug-and-play model."

"The ease of deployment on Kubernetes, the seamless integration for orchestration of various pipelines, and the visual dashboard that simplifies operations even for non-specialists such as quality analysts."

"The product is very user-friendly."

"The solution's most valuable feature is that it allows us to use different batch data sources, retrieve the data, and then do the data processing, after which we can convert and store it in the target."

"The dashboards in Spring Cloud Dataflow are quite valuable."

"The most valuable feature is real-time streaming."

"The most valuable features of Spring Cloud Data Flow are the simple programming model, integration, dependency Injection, and ability to do any injection. Additionally, auto-configuration is another important feature because we don't have to configure the database and or set up the boilerplate in the database in every project. The composability is good, we can create small workloads and compose them in any way we like."

Cons

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

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

"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."

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

"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 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."

"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."

More Amazon MSK cons

"Spring Cloud Data Flow could improve the user interface. We can drag and drop in the application for the configuration and settings, and deploy it right from the UI, without having to run a CI/CD pipeline. However, that does not work with Kubernetes, it only works when we are working with jars as the Spring Cloud Data Flow applications."

"Spring Cloud Data Flow is not an easy-to-use tool, so improvements are required."

"I would improve the dashboard features as they are not very user-friendly."

"Some of the features, like the monitoring tools, are not very mature and are still evolving."

"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."

"There were instances of deployment pipelines getting stuck, and the dashboard not always accurately showing the application status, requiring manual intervention such as rerunning applications or refreshing the dashboard."

"The solution's community support could be improved."

"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."

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 product that can be used free of charge."

"The solution provides value for money, and we are currently using its community edition."

"If you want support from Spring Cloud Data Flow there is a fee. The Spring Framework is open-source and this is a free solution."

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Top Industries

By visitors reading reviews

Financial Services Firm

23%

Computer Software Company

13%

Manufacturing Company

Construction Company

Financial Services Firm

22%

Computer Software Company

13%

Retailer

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	3
Midsize Enterprise	1
Large Enterprise	5

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?

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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 needs improvement with Spring Cloud Data Flow?

There were instances of deployment pipelines getting stuck, and the dashboard not always accurately showing the application status, requiring manual intervention such as rerunning applications or r...

See all answers

What is your primary use case for Spring Cloud Data Flow?

We had a project for content management, which involved multiple applications each handling content ingestion, transformation, enrichment, and storage for different customers independently. We want...

See all answers

What advice do you have for others considering Spring Cloud Data Flow?

I would definitely recommend Spring Cloud Data Flow. It requires minimal additional effort or time to understand how it works, and even non-specialists can use it effectively with its friendly docu...

See all answers

Comparisons

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Compared 27% of the time

Apache Flink vs Amazon MSK

Compared 15% of the time

Confluent vs Amazon MSK

Compared 12% of the time

Amazon Kinesis vs Amazon MSK

Compared 8% of the time

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Apache Flink vs Spring Cloud Data Flow

Compared 29% of the time

TIBCO BusinessWorks vs Spring Cloud Data Flow

Compared 7% of the time

Apache Kafka vs Spring Cloud Data Flow

Compared 5% of the time

Apache Spark Streaming vs Spring Cloud Data Flow

Compared 5% of the time

MuleSoft Anypoint Platform vs Spring Cloud Data Flow

Compared 5% of the time

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Product Reports

Buyer's Guide

Amazon MSK

December 2025

Download Amazon MSK product report

Buyer's Guide

Spring Cloud Data Flow

December 2025

Download Spring Cloud Data Flow product report

Also Known As

Amazon Managed Streaming for Apache Kafka

No data available

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)

Spring Cloud Data Flow is a toolkit for building data integration and real-time data processing pipelines.
Pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. This makes Spring Cloud Data Flow suitable for a range of data processing use cases, from import/export to event streaming and predictive analytics. Use Spring Cloud Data Flow to connect your Enterprise to the Internet of Anything—mobile devices, sensors, wearables, automobiles, and more.

Broadcom

Sample Customers

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers

Information Not Available

Buyer's Guide

Amazon MSK vs. Spring Cloud Data Flow

December 2025

Free Report: Amazon MSK vs. Spring Cloud Data Flow

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