Amazon MSK vs Spring Cloud Data Flow comparison

Why PeerSpot?

Amazon Web Services (AWS) and Broadcom are both solutions in the Streaming Analytics category. Amazon Web Services (AWS) is ranked #14 with an average rating of 7.0, while Broadcom is ranked #18 with an average rating of 7.5. Amazon Web Services (AWS) holds a 3.9% mindshare in SA, compared to Broadcom’s 2.5% 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

2,770 Views
2,715 Comparison Views

93% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

4,715 Views
1,509 Comparison Views

88% willing to recommend

Amazon MSK

Spring Cloud Data Flow

Comparison Buyer's Guide

Download the report

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: September 2026).

Buyer's Guide

Amazon MSK vs. Spring Cloud Data Flow

September 2026

Download the complete report

Helped 913,806 peers since 2012

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

Spring Cloud Data Flow

Ranking in Streaming Analytics

18th

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Integration (33rd)

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 Spring Cloud Data Flow is 2.5%, down from 4.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Amazon MSK	3.9%
Spring Cloud Data Flow	2.5%
Other	93.6%

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

NitinGoyal

Engineering Lead at Naukri.com

Has a plug-and-play model and provides good robustness and scalability

The solution's community support could be improved. I don't know why the Spring Cloud Data Flow community is not very strong. Community support is very limited whenever you face any problem or are stuck somewhere. I'm not sure whether it has improved in the last six months because this pipeline was set up almost two years ago. I struggled with that a lot. For example, there was limited support whenever I got an exception and sought help from Stack Overflow or different forums. Interacting with Kubernetes needs a few certificates. You need to define all the certificates within your application. With the help of those certificates, your Java application or Spring Cloud Data Flow can interact with Kubernetes. I faced a lot of hurdles while placing those certificates. Despite following the official documentation to define all the replicas, readiness, and liveliness probes within the Spring Cloud Data Flow application, it was not working. So, I had to troubleshoot while digging in and debugging the internals of Spring Cloud Data Flow at that time. It was just a configuration mismatch, and I was doing nothing weird. There was a small spelling difference between how Spring Cloud Data Flow was expecting it and how I passed it. I was just following the official documentation.

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."

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

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

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

"It is a stable product."

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

"My advice to others is this solution is straightforward and the integration is flawless."

"Amazon MSK has good integration because our team has been undergoing significant changes. Coupling it with MSK within AWS is helpful. We don't have to set up additionals or monitor external environments. This"

More Amazon MSK pros

"The product is very user-friendly."

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

"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."

"Overall, Spring Cloud Data Flow is a really good solution and a lot cheaper than a lot of infrastructure provided by big companies like Google or Amazon."

"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 most valuable feature is real-time streaming."

"This product will assist us in saving costs in many ways: No longer need to continue paying high fees for proprietary software, reduce the number of software engineers needed to support the product, and achieve faster time to market by using this product for our middleware."

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

More Spring Cloud Data Flow pros

Cons

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

"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."

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

"It does not autoscale. Because if you do keep it manually when you add a note to the cluster and then you register it, then it is scalable, but the fact that you have to go and do it, I think, makes it, again, a bit of some operational overhead when managing the cluster."

"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 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."

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

More Amazon MSK cons

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

"The visual user interface could use some help; it needs improvement."

"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."

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

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

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

"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."

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

More Spring Cloud Data Flow 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."

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

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

"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."

See which vendors are best for you

Use our free recommendation engine to learn which Streaming Analytics solutions are best for your needs.

See recommendations

913,806 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

16%

Manufacturing Company

10%

Comms Service Provider

Construction Company

Financial Services Firm

16%

Computer Software Company

10%

Outsourcing Company

Retailer

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	3
Midsize Enterprise	1
Large Enterprise	5

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 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

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

Databricks vs Amazon MSK

Compared 3% of the time

More Amazon MSK Competitors

Apache Flink vs Spring Cloud Data Flow

Compared 7% of the time

TIBCO Spotfire vs Spring Cloud Data Flow

Compared 6% of the time

Cloudera DataFlow vs Spring Cloud Data Flow

Compared 6% of the time

TIBCO BusinessWorks vs Spring Cloud Data Flow

Compared 4% of the time

Apache Spark Streaming vs Spring Cloud Data Flow

Compared 4% of the time

More Spring Cloud Data Flow Competitors

Product Reports

Buyer's Guide

Amazon MSK

September 2026

Download Amazon MSK product report

Buyer's Guide

Spring Cloud Data Flow

August 2026

Download Spring Cloud Data Flow product report

Also Known As

Amazon Managed Streaming for Apache Kafka

No data available

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)

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

September 2026

Free Report: Amazon MSK vs. Spring Cloud Data Flow

Find out what your peers are saying about Amazon MSK vs. Spring Cloud Data Flow and other solutions. Updated: September 2026.

DOWNLOAD NOW

913,806 professionals have used our research since 2012.

See our Amazon MSK vs. Spring Cloud Data Flow report.

See our list of best Streaming Analytics vendors.

We monitor all Streaming Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.