ETL Solutions Transformation Manager vs Spring Cloud Data Flow comparison

ETL Solutions and Broadcom are both solutions in the Data Integration category. ETL Solutions is ranked #54, while Broadcom is ranked #22 with an average rating of 7.8. ETL Solutions holds a 0.9% mindshare in DI, compared to Broadcom’s 1.1% mindshare. Additionally, 100% of ETL Solutions users are willing to recommend the solution, compared to 88% of Broadcom users who would recommend it.

ETL Solutions Transformatio...

Read 3 ETL Solutions Transformation Manager reviews

1,352 Views
906 Comparison Views

100% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

3,140 Views
1,601 Comparison Views

88% willing to recommend

ETL Solutions Transformatio...

Spring Cloud Data Flow

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Executive SummaryUpdated on Dec 19, 2024

ETL Solutions Transformation Manager and Spring Cloud Data Flow compete in data integration tools. ETL Solutions Transformation Manager seems to have the upper hand in pricing and support, while Spring Cloud Data Flow stands out in feature robustness.

Features: ETL Solutions Transformation Manager offers flexibility for complex data transformations, extensive support for legacy systems, and customizable workflows. Spring Cloud Data Flow features a microservices architecture, scalability with cloud-native environments, and a broad range of connectors for modern cloud applications.

Ease of Deployment and Customer Service: ETL Solutions Transformation Manager offers easy deployment and responsive customer support which is ideal for organizations with existing infrastructure. Spring Cloud Data Flow's deployment involves cloud-native environments, providing long-term scalability but requiring more initial setup.

Pricing and ROI: ETL Solutions Transformation Manager is recognized for its competitive pricing, appealing to budget-conscious organizations with a focus on high ROI. Spring Cloud Data Flow, while having higher initial costs, delivers significant ROI because of its advanced features and scalability.

To learn more, read our detailed ETL Solutions Transformation Manager vs. Spring Cloud Data Flow Report (Updated: March 2026).

Buyer's Guide

ETL Solutions Transformation Manager vs. Spring Cloud Data Flow

March 2026

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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

ETL Solutions Transformatio...

Ranking in Data Integration

54th

Average Rating

9.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Spring Cloud Data Flow

Ranking in Data Integration

22nd

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Streaming Analytics (10th)

Mindshare comparison

As of March 2026, in the Data Integration category, the mindshare of ETL Solutions Transformation Manager is 0.9%, up from 0.2% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.1%, up from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Spring Cloud Data Flow	1.1%
ETL Solutions Transformation Manager	0.9%
Other	98.0%

Data Integration

Featured Reviews

Ravi Kuppusamy

CEO and Founder at BAssure Solutions

It lets us create models so we can generate real-time predictions and insights for a our clients

Transformation Manager reporting could be better. There are better options for reporting tools these days. We use Microsoft BI sometimes, but Tableau is becoming too expensive. Microsoft BI's visualization features are maturing. I would like it if we could set the solution up to process and respond to real-time events. For example, say I want to configure an app to run based on the mileage a car has driven, and I configure the metering system, so the event occurs every 15 days. Let's say we want to automatically send an alert to EMS, police, etc. if a car gets into an accident. Transformation Manager is more of a conventional tool for reporting, extracting volume, bulk loading, etc. but there should be more provisions for dealing with real-time events, creating some insights, and dealing with perishable data. Ten minutes after the accident, the data doesn't have value. It has value before you saved the person.

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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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Quotes from Members

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

Pros

"Transformation Manager is the backbone of every data pipeline these days because the solution has been on the market for 20 to 30 years, and we use it for various industries, including financial services, manufacturing, healthcare, etc."

"Back in the day, we could only get reports and analyze what happened after the fact, but today now we can generate real-time insights. Transformation Manager feeds your data science projects. We generate models and then give them to the clients, so they can come up with real-time predictions and recommendations in addition to reporting."

"It is a reliable solution."

"It is among the best, even if not widely known."

"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 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 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 dashboards in Spring Cloud Dataflow are quite valuable."

"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."

More Spring Cloud Data Flow pros

Cons

"There is room for improvement in the solution's visualization tool."

"Transformation Manager reporting could be better. There are better options for reporting tools these days. We use Microsoft BI sometimes, but Tableau is becoming too expensive. Microsoft BI's visualization features are maturing."

"They should build a functional architecture based on queuing."

"We get decent support. It's okay but not great."

"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."

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

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

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

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

More Spring Cloud Data Flow cons

Pricing and Cost Advice

"It is an expensive solution."

"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."

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Top Industries

By visitors reading reviews

Computer Software Company

15%

Outsourcing Company

13%

Performing Arts

10%

Retailer

10%

Financial Services Firm

18%

Computer Software Company

12%

Retailer

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	1
Large Enterprise	5

Questions from the Community

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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...

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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...

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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

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Product Reports

Buyer's Guide

Data Integration

February 2026

ETL Solutions Transformation Manager report

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Buyer's Guide

Spring Cloud Data Flow

February 2026

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Also Known As

Transformation Manager

No data available

Overview

Transformation Manager is an integrated development toolkit that is used to build data migration and data integration solutions more efficiently. A metadata-driven code generator, Transformation Manager provides users with the ability to generate lightweight, easy-to-deploy code. It combines a Graphical User Interface with a statement-driven mapping language. The Transformation Manager software derives metadata from the elements, attributes and relationships in a source and target model. Transformation Manager then uses rules specified by Simple Mapping Language (SML), which is specifically designed for implementing data transformation projects, to generate code written in Java.

ETL Solutions

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

Honda, BNP Paribas, RBS, JPMorgan, Volkswagen, Thorn Lighting, OpenSpirit, Rolls-Royce, Ulster Bank

Information Not Available

Buyer's Guide

ETL Solutions Transformation Manager vs. Spring Cloud Data Flow

March 2026

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