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ETL Solutions Transformation Manager vs Spring Cloud Data Flow 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

ETL Solutions Transformatio...
Ranking in Data Integration
33rd
Average Rating
9.0
Reviews Sentiment
6.8
Number of Reviews
3
Ranking in other categories
No ranking in other categories
Spring Cloud Data Flow
Ranking in Data Integration
24th
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
9
Ranking in other categories
Streaming Analytics (9th)
 

Mindshare comparison

As of April 2025, in the Data Integration category, the mindshare of ETL Solutions Transformation Manager is 0.2%, up from 0.2% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.1%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

Ravi Kuppusamy - PeerSpot reviewer
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.
NitinGoyal - PeerSpot reviewer
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.

Quotes from Members

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

Pros

"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 product is very user-friendly."
"The most valuable feature is real-time streaming."
"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."
"The dashboards in Spring Cloud Dataflow are quite valuable."
"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 best thing I like about Spring Cloud Data Flow is its plug-and-play model."
"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."
 

Cons

"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."
"There is room for improvement in the solution's visualization tool."
"I would improve the dashboard features as they are not very user-friendly."
"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."
"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."
"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."
"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."
 

Pricing and Cost Advice

"It is an expensive solution."
"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."
"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
28%
Financial Services Firm
16%
Healthcare Company
8%
Educational Organization
6%
Financial Services Firm
26%
Computer Software Company
17%
Retailer
7%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for ETL Solutions Transformation Manager?
ETL Solutions Transformation Manager is much more affordable than other solutions like AWS, Blue, or Informatica. Even though some competitors may offer seemingly economical pricing, the resource c...
What needs improvement with ETL Solutions Transformation Manager?
There is room for improvement in the solution's visualization tool. Currently, it provides basic reports and the ability to create graphs and dashboards, but I'm looking forward to more robust anal...
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...
 

Also Known As

Transformation Manager
No data available
 

Overview

 

Sample Customers

Honda, BNP Paribas, RBS, JPMorgan, Volkswagen, Thorn Lighting, OpenSpirit, Rolls-Royce, Ulster Bank
Information Not Available
Find out what your peers are saying about ETL Solutions Transformation Manager vs. Spring Cloud Data Flow and other solutions. Updated: April 2025.
847,772 professionals have used our research since 2012.