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Spring Cloud Data Flow vs TetraScience comparison

 

Comparison Buyer's Guide

Executive Summary

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
9
Ranking in other categories
Streaming Analytics (10th)
TetraScience
Ranking in Data Integration
56th
Average Rating
6.6
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of March 2026, in the Data Integration category, the mindshare of Spring Cloud Data Flow is 1.1%, up from 1.0% compared to the previous year. The mindshare of TetraScience is 0.3%. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Spring Cloud Data Flow1.1%
TetraScience0.3%
Other98.6%
Data Integration
 

Featured Reviews

NitinGoyal - PeerSpot reviewer
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.
Varun Khandavalli - PeerSpot reviewer
Senior Specialist Engineering Dev. & Integration at a manufacturing company with 10,001+ employees
Efficient data integration and good automation with challenging configurability
The application has a difficult-to-use parsing capability, which requires a lot of reengineering when the use case isn't specifically met. The application also lacks capabilities within its terminal commands that are not available in their GUI. It requires a lot of configurability, which could be streamlined for an enterprise application user.

Quotes from Members

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

Pros

"Overall, Spring Cloud Data Flow is a really good solution and a lot cheaper than a lot of infrastructure provided by big companies like Google or Amazon."
"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 dashboards in Spring Cloud Dataflow are quite valuable."
"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 most valuable feature is real-time streaming."
"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."
"The ingestion engines were pretty good."
"The crawler agents they provide, as well as TetraScience exclusive parsers, allow for specific instruments that we use in our labs with proprietary formats to extract data and put it into more standard formats for various purposes."
 

Cons

"The documentation on offer is not that good."
"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."
"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 visual user interface could use some help; it needs improvement."
"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."
"Spring Cloud Data Flow is not an easy-to-use tool, so improvements are required."
"While functional during ingestion workflows, the automation toolkit required manual processes."
"The application has a difficult-to-use parsing capability, which requires a lot of reengineering when the use case isn't specifically met."
 

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."
"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."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
12%
Retailer
8%
Manufacturing Company
6%
Construction Company
34%
Computer Software Company
12%
Pharma/Biotech Company
9%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise1
Large Enterprise5
No data available
 

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 needs improvement with TetraScience?
The application has a difficult-to-use parsing capability, which requires a lot of reengineering when the use case isn't specifically met. The application also lacks capabilities within its termina...
What is your primary use case for TetraScience?
TetraScience is a platform that integrates instruments into a laboratory environment into other software applications that can help leverage the data. In most pharma companies, the application is u...
What advice do you have for others considering TetraScience?
I would approach with caution. The platform has a high knowledge gap and the proprietary nature of its parsers and crawling agents. Before approaching TetraScience, have your use case in hand and u...
 

Overview

Find out what your peers are saying about Spring Cloud Data Flow vs. TetraScience and other solutions. Updated: March 2026.
885,311 professionals have used our research since 2012.