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Spring Cloud Data Flow vs StreamSets comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 2024

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
21st
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
9
Ranking in other categories
Streaming Analytics (10th)
StreamSets
Ranking in Data Integration
22nd
Average Rating
8.4
Reviews Sentiment
7.0
Number of Reviews
21
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of October 2025, in the Data Integration category, the mindshare of Spring Cloud Data Flow is 1.2%, up from 1.0% compared to the previous year. The mindshare of StreamSets is 1.5%, down from 1.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Market Share Distribution
ProductMarket Share (%)
Spring Cloud Data Flow1.2%
StreamSets1.5%
Other97.3%
Data Integration
 

Featured Reviews

Alokik Gupta - PeerSpot reviewer
Effective microservice and task management but needs more dashboard features
The dashboards in Spring Cloud Dataflow are quite valuable. By injecting the dependency of Spring Cloud Dataflow into our Spring Boot application and annotating it with 'enable task annotation', we can manage tasks effectively. Additionally, the platform allows us to create pipelines and use microservices like a logical AND gate, giving us greater control over our microservices.
Ved Prakash Yadav - PeerSpot reviewer
Useful for data transformation and helps with column encryption
We use various tools and alerting systems to notify us of pipeline errors or failures. StreamSets supports data governance and compliance by allowing us to encrypt incoming data based on specified rules. We can easily encrypt columns by providing the column name and hash key. If you're considering using StreamSets for the first time, I would advise first understanding why you want to use it and how it will benefit you. If you're dealing with change tracking or handling large amounts of data, it could be cost-effective compared to services like Amazon. It's easy to schedule and manage tasks with the tool, and you can enhance your skills as an ETL developer. You can easily migrate traditional pipelines built on platforms like Informatica or Talend to StreamSets. I rate the overall solution an eight out of ten.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The product is very user-friendly."
"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 best thing I like about Spring Cloud Data Flow is its plug-and-play model."
"The most valuable feature is real-time streaming."
"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 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."
"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."
"StreamSets data drift feature gives us an alert upfront so we know that the data can be ingested. Whatever the schema or data type changes, it lands automatically into the data lake without any intervention from us, but then that information is crucial to fix for downstream pipelines, which process the data into models, like Tableau and Power BI models. This is actually very useful for us. We are already seeing benefits. Our pipelines used to break when there were data drift changes, then we needed to spend about a week fixing it. Right now, we are saving one to two weeks. Though, it depends on the complexity of the pipeline, we are definitely seeing a lot of time being saved."
"The scheduling within the data engineering pipeline is very much appreciated, and it has a wide range of connectors for connecting to any data sources like SQL Server, AWS, Azure, etc. We have used it with Kafka, Hadoop, and Azure Data Factory Datasets. Connecting to these systems with StreamSets is very easy."
"StreamSets is the leader in the market."
"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."
"I have used Data Collector, Transformer, and Control Hub products from StreamSets. What I really like about these products is that they're very user-friendly. People who are not from a technological or core development background find it easy to get started and build data pipelines and connect to the databases. They would be comfortable like any technical person within a couple of weeks."
"The entire user interface is very simple and the simplicity of creating pipelines is something that I like very much about it. The design experience is very smooth."
"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."
 

Cons

"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."
"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."
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."
"I would improve the dashboard features as they are not very user-friendly."
"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."
"The documentation is inadequate and has room for improvement because the technical support does not regularly update their documentation or the knowledge base."
"The design experience is the bane of our existence because their documentation is not the best. Even when they update their software, they don't publish the best information on how to update and change your pipeline configuration to make it conform to current best practices. We don't pay for the added support. We use the "freeware version." The user community, as well as the documentation they provide for the standard user, are difficult, at best."
"StreamSet works great for batch processing but we are looking for something that is more real-time. We need latency in numbers below milliseconds."
"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."
"Visualization and monitoring need to be improved and refined."
"The software is very good overall. Areas for improvement are the error logging and the version history. I would like to see better, more detailed error logging information."
"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."
"We've seen a couple of cases where it appears to have a memory leak or a similar problem."
 

Pricing and Cost Advice

"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."
"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."
"We use the free version. It's great for a public, free release. Our stance is that the paid support model is too expensive to get into. They should honestly reevaluate that."
"I believe the pricing is not equitable."
"It's not so favorable for small companies."
"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."
"The pricing is affordable for any business."
"We are running the community version right now, which can be used free of charge."
"There are two editions, Professional and Enterprise, and there is a free trial. We're using the Professional edition and it is competitively priced."
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Top Industries

By visitors reading reviews
Financial Services Firm
24%
Computer Software Company
16%
Retailer
8%
Manufacturing Company
5%
Computer Software Company
11%
Insurance Company
9%
Financial Services Firm
9%
Manufacturing Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise1
Large Enterprise5
By reviewers
Company SizeCount
Small Business9
Midsize Enterprise2
Large Enterprise11
 

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...
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...
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...
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...
What needs improvement with StreamSets?
One issue I observed with StreamSets is that the memory runs out quickly when processing large volumes of data. Because of this memory issue, we have to upgrade our EC2 boxes in the Amazon AWS infr...
What is your primary use case for StreamSets?
We are using StreamSets for batch loading.
 

Overview

 

Sample Customers

Information Not Available
Availity, BT Group, Humana, Deluxe, GSK, RingCentral, IBM, Shell, SamTrans, State of Ohio, TalentFulfilled, TechBridge
Find out what your peers are saying about Spring Cloud Data Flow vs. StreamSets and other solutions. Updated: September 2025.
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