Spring Cloud Data Flow vs StreamSets comparison

VMware and IBM are both solutions in the Data Integration category. VMware is ranked #23 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

1,465 Views
1,098 Comparison Views

88% willing to recommend

StreamSets

Read 20 StreamSets reviews

2,525 Views
1,707 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: March 2025).

Buyer's Guide

Spring Cloud Data Flow vs. StreamSets

March 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

23rd

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

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of March 2025, in the Data Integration category, the mindshare of Spring Cloud Data Flow is 1.1%, up from 0.8% 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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Nantabo Jackie

Sales Manager at Soft Hostings Limited

Simplified pipelines and helped us break down data silos within our organization

The design experience when implementing batch streaming or ECL pipelines is very easy and straightforward. When we initially attempted to integrate StreamSets with Kafka, it was somewhat challenging until we consulted the documentation, after which it became straightforward. We use StreamSets to move data into modern analytics platforms. Moving the data into modern analytics platforms is still complex. It requires a lot of understanding of logic. StreamSets enables us to build data pipelines without knowing how to code. StreamSets' ability to build data pipelines without requiring us to know complex programming is very important, as it allows us to focus on our projects without spending time writing code. StreamSets' Transformer for Snowflake is simple to use for designing both simple and complex transformation logic. StreamSets' Transformer for Snowflake is extremely important to me as it helps me to connect external data sources and keep my internal workflow organized. Transformer for Snowflake's functionality is a perfect ten out of ten. It is important and cost-effective that Transformer for Snowflake is a serverless engine embedded within the platform, as without this feature, it would be very expensive. This feature helps us to sell at lower budget costs, which would otherwise be at a high cost with other servers. StreamSets has helped improve our organization. StreamSets simplified pipelines for our organization. It is easier to complete a project when we know where and how to start, and working with the team remotely makes it more efficient. This helps us to save time and be more organized when creating data pipelines. Being a structured company that produces reliable resources for our application benefits both our clients and contacts. StreamSets' built-in data drift resilience plays a part in our ETL operations. With prior knowledge, the built-in data drift resilience is very effective, but it can be challenging to implement without the preexisting knowledge. The built-in data drift resilience reduced the time it takes us to fix data drift breakages by 45 percent. StreamSets helped us break down data silos within our organization. The use of StreamSets to break down data silos enabled us to be confident in the services and products we provide, as well as the real-time streaming we offer. This has had a positive impact on our business, as it allowed us to accurately determine the analytics we need to present to stakeholders, clients, and our sources while ensuring that the process is secure and transparent. StreamSets saved us time because anyone can use StreamSets not just developers. We can save around 40 percent of our time. StreamSets' reusable assets helped us reduce workload by around 25 percent. StreamSets saved us money by not having to hire developers with specialized skills. We saved around $2,000 US. StreamSets helped us scale our data operations. Since StreamSets makes it easy to scale our data operations, it enabled us to know exactly where to start at any time. We are aware of the timeline for completing the project, and depending on our familiarity with the software, we can come up with a solution quickly.

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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 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 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."

"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 most valuable feature is real-time streaming."

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

"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."

"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."

"The most valuable feature is the pipelines because they enable us to pull in and push out data from different sources and to manipulate and clean things up within them."

"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 customize it to do what you need. Many other tools have started to use features similar to those introduced by StreamSets, like automated workflows that are easy to set up."

"The most valuable would be the GUI platform that I saw. I first saw it at a special session that StreamSets provided towards the end of the summer. I saw the way you set it up and how you have different processes going on with your data. The design experience seemed to be pretty straightforward to me in terms of how you drag and drop these nodes and connect them with arrows."

"The best feature that I really like is the integration."

"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."

"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."

"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."

More StreamSets pros

Cons

"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 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."

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

"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."

"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."

"The execution engine could be improved. When I was at their session, they were using some obscure platform to run. There is a controller, which controls what happens on that, but you should be able to easily do this at any of the cloud services, such as Google Cloud. You shouldn't have any issues in terms of how to run it with their online development platform or design platform, basically their execution engine. There are issues with that."

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

"Currently, we can only use the query to read data from SAP HANA. What we would like to see, as soon as possible, is the ability to read from multiple tables from SAP HANA. That would be a really good thing that we could use immediately. For example, if you have 100 tables in SQL Server or Oracle, then you could just point it to the schema or the 100 tables and ingestion information. However, you can't do that in SAP HANA since StreamSets currently is lacking in this. They do not have a multi-table feature for SAP HANA. Therefore, a multi-table origin for SAP HANA would be helpful."

"We've seen a couple of cases where it appears to have a memory leak or a similar problem."

"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."

"The logging mechanism could be improved. If I am working on a pipeline, then create a job out of it and it is running, it will generate constant logs. So, the logging mechanism could be simplified. Now, it is a bit difficult to understand and filter the logs. It takes some time."

"One area for improvement could be the cloud storage server speed, as we have faced some latency issues here and there."

"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."

More StreamSets cons

Pricing and Cost Advice

"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 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."

"It has a CPU core-based licensing, which works for us and is quite good."

"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."

"StreamSets is an expensive solution."

"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."

"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."

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

"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."

More StreamSets pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

25%

Computer Software Company

17%

Manufacturing Company

Retailer

Financial Services Firm

14%

Computer Software Company

11%

Manufacturing Company

10%

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...

See all answers

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...

See all answers

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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Compared 5% of the time

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Compared 4% of the time

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Compared 9% of the time

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Compared 8% of the time

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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

March 2025

Free Report: Spring Cloud Data Flow vs. StreamSets

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