Spring Cloud Data Flow vs StreamSets comparison

VMware and IBM are both solutions in the Data Integration category. VMware is ranked #24 with an average rating of 7.7, while IBM is ranked #15 with an average rating of 8.4. VMware holds a 1.1% mindshare in DI, compared to IBM’s 1.6% mindshare. Additionally, 88% of VMware users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

1,421 Views
1,057 Comparison Views

88% willing to recommend

StreamSets

Read 21 StreamSets reviews

2,378 Views
1,645 Comparison Views

100% willing to recommend

Spring Cloud Data Flow

StreamSets

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Executive SummaryUpdated on Dec 19, 2024

StreamSets and Spring Cloud Data Flow compete in the data integration and orchestration category. StreamSets offers advantages in user-friendliness and data transformation capabilities, making it the preferred choice for those emphasizing ease of use and flexibility in design.

Features: StreamSets offers a drag-and-drop interface for data pipeline creation, supports both batch and streaming data processing, and provides robust data transformation capabilities at the source. Its control hub facilitates graphical design with flexibility. Spring Cloud Data Flow is notable for its microservices orchestration, integration with Kubernetes, and support for low-resource execution using a simple programming model.

Room for Improvement: StreamSets needs better integration with non-Java platforms, enhanced memory management, and improvements in its security features and user interface. It also requires expanded SAP HANA capabilities and more effective data drift handling. Spring Cloud Data Flow could benefit from better community support, enhanced documentation, and improved UI for Kubernetes integration. Additional support for non-Java languages would also be beneficial.

Ease of Deployment and Customer Service: StreamSets provides versatile deployment options across public and hybrid clouds and generally responsive support, although complex issues may require time. Spring Cloud Data Flow is well-suited for private cloud environments but relies heavily on community forums for support, making professional assistance necessary for more challenging deployments. StreamSets facilitates easier cloud deployments, while Spring Cloud Data Flow is ideal for those adept at self-support in private solutions.

Pricing and ROI: StreamSets offers a range of licensing options, including open-source and commercial, but faces criticism for its cost structure, making it less attractive to smaller enterprises. It offers significant ROI for larger organizations in need of comprehensive ETL solutions. Spring Cloud Data Flow provides value through its free open-source model, being cost-effective for community edition users. StreamSets reports increased sales of up to 50%, while Spring Cloud Data Flow is ideal for budget-conscious users seeking open-source capabilities.

To learn more, read our detailed Spring Cloud Data Flow vs. StreamSets Report (Updated: April 2025).

Buyer's Guide

Spring Cloud Data Flow vs. StreamSets

April 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

Spring Cloud Data Flow

Ranking in Data Integration

24th

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Streaming Analytics (9th)

StreamSets

Ranking in Data Integration

15th

Average Rating

8.4

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2025, in the Data Integration category, the mindshare of Spring Cloud Data Flow is 1.1%, up from 0.9% compared to the previous year. The mindshare of StreamSets is 1.6%, up from 1.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

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.

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Karthik Rajamani

Principal Engineer at Tata Consultancy Services

Integrates with different enterprise systems and enables us to easily build data pipelines without knowing how to code

There are a few things that can be better. We create pipelines or jobs in StreamSets Control Hub. It is a great feature, but if there is a way to have a folder structure or organize the pipelines and jobs in Control Hub, it would be great. I submitted a ticket for this some time back. There are certain features that are only available at certain stages. For example, HTTP Client has some great features when it is used as a processor, but those features are not available in HTTP Client as a destination. There could be some improvements on the group side. Currently, if I want to know which users are a part of certain groups, it is not straightforward to see. You have to go to each and every user and check the groups he or she is a part of. They could improve it in that direction. Currently, we have to put in a manual effort. In case something goes wrong, we have to go to each and every user account to check whether he or she is a part of a certain group or not.

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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

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

"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 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 product is very user-friendly."

"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 dashboards in Spring Cloud Dataflow are quite valuable."

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

"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."

"The ETL capabilities are very useful for us. We extract and transform data from multiple data sources, into a single, consistent data store, and then we put it in our systems. We typically use it to connect our Apache Kafka with data lakes. That process is smooth and saves us a lot of time in our production systems."

"StreamSets Transformer is a good feature because it helps you when you are developing applications and when you don't want to write a lot of code. That is the best feature overall."

"The ability to have a good bifurcation rate and fewer mistakes is valuable."

"One of the things I like is the data pipelines. They have a very good design. Implementing pipelines is very straightforward. It doesn't require any technical skill."

"Also, the intuitive canvas for designing all the streams in the pipeline, along with the simplicity of the entire product are very big pluses for me. The software is very simple and straightforward. That is something that is needed right now."

"For me, the most valuable features in StreamSets have to be the Data Collector and Control Hub, but especially the Data Collector. That feature is very elegant and seamlessly works with numerous source systems."

"I really appreciate the numerous ready connectors available on both the source and target sides, the support for various media file formats, and the ease of configuring and managing pipelines centrally."

"StreamSets’ data drift resilience has reduced the time it takes us to fix data drift breakages. For example, in our previous Hadoop scenario, when we were creating the Sqoop-based processes to move data from source to destinations, we were getting the job done. That took approximately an hour to an hour and a half when we did it with Hadoop. However, with the StreamSets, since it works on a data collector-based mechanism, it completes the same process in 15 minutes of time. Therefore, it has saved us around 45 minutes per data pipeline or table that we migrate. Thus, it reduced the data transfer, including the drift part, by 45 minutes."

More StreamSets pros

Cons

"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 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."

"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."

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

"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."

"Sometimes, it is not clear at first how to set up nodes. A site with an explanation of how each node works would be very helpful."

"There aren't enough hands-on labs, and debugging is also an issue because it takes a lot of time. Logs are not that clear when you are debugging, and you can only select a single source for a pipeline."

"StreamSet works great for batch processing but we are looking for something that is more real-time. We need latency in numbers below milliseconds."

"If you use JDBC Lookup, for example, it generally takes a long time to process data."

"In terms of the product, I don't think there is any room for improvement because it is very good. One small area of improvement that is very much needed is on the knowledge base side. Sometimes, it is not very clear how to set up a certain process or a certain node for a person who's using the platform for the first time."

"I would like to see it integrate with other kinds of platforms, other than Java. We're going to have a lot of applications using .NET and other languages or frameworks. StreamSets is very helpful for the old Java platform but it's hard to integrate with the other platforms and frameworks."

"StreamSets should provide a mechanism to be able to perform data quality assessment when the data is being moved from one source to the target."

"The monitoring visualization is not that user-friendly. It should include other features to visualize things, like how many records were streamed from a source to a destination on a particular date."

More StreamSets cons

Pricing and Cost Advice

"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."

"We are running the community version right now, which can be used free of charge."

"The overall cost is very flexible so it is not a burden for our organization... However, the cost should be improved. For small and mid-size organizations it might be a challenge."

"The licensing is expensive, and there are other costs involved too. I know from using the software that you have to buy new features whenever there are new updates, which I don't really like. But initially, it was very good."

"The pricing is too fixed. It should be based on how much data you need to process. Some businesses are not so big that they process a lot of data."

"It's not so favorable for small companies."

"Its pricing is pretty much up to the mark. For smaller enterprises, it could be a big price to pay at the initial stage of operations, but the moment you have the Seed B or Seed C funding and you want to scale up your operations and aren't much worried about the funds, at that point in time, you would need a solution that could be scaled."

"StreamSets Data Collector is open source. One can utilize the StreamSets Data Collector, but the Control Hub is the main repository where all the jobs are present. Everything happens in Control Hub."

"There are different versions of the product. One is the corporate license version, and the other one is the open-source or free version. I have been using the corporate license version, but they have recently launched a new open-source version so that anybody can create an account and use it. The licensing cost varies from customer to customer. I don't have a lot of input on that. It is taken care of by PMO, and they seem fine with its pricing model. It is being used enterprise-wide. They seem to have got a good deal for StreamSets."

More StreamSets pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

26%

Computer Software Company

17%

Retailer

Manufacturing Company

Financial Services Firm

14%

Computer Software Company

11%

Manufacturing Company

Insurance Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

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...

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What do you like most about StreamSets?

The best thing about StreamSets is its plugins, which are very useful and work well with almost every data source. It's also easy to use, especially if you're comfortable with SQL. You can customiz...

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What needs improvement with StreamSets?

We often faced problems, especially with SAP ERP. We struggled because many columns weren't integers or primary keys, which StreamSets couldn't handle. We had to restructure our data tables, which ...

See all answers

What is your primary use case for StreamSets?

StreamSets is used for data transformation rather than ETL processes. It focuses on transforming data directly from sources without handling the extraction part of the process. The transformed data...

See all answers

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Product Reports

Buyer's Guide

Spring Cloud Data Flow

March 2025

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Buyer's Guide

StreamSets

March 2025

Download StreamSets product report

Overview

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.

VMware

StreamSets is a data integration platform that enables organizations to efficiently move and process data across various systems. It offers a user-friendly interface for designing, deploying, and managing data pipelines, allowing users to easily connect to various data sources and destinations. StreamSets also provides real-time monitoring and alerting capabilities, ensuring that data is flowing smoothly and any issues are quickly addressed.

IBM

Sample Customers

Information Not Available

Availity, BT Group, Humana, Deluxe, GSK, RingCentral, IBM, Shell, SamTrans, State of Ohio, TalentFulfilled, TechBridge

Buyer's Guide

Spring Cloud Data Flow vs. StreamSets

April 2025

Free Report: Spring Cloud Data Flow vs. StreamSets

Find out what your peers are saying about Spring Cloud Data Flow vs. StreamSets and other solutions. Updated: April 2025.

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