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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
21st
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
9
Ranking in other categories
Streaming Analytics (10th)
TetraScience
Ranking in Data Integration
49th
Average Rating
6.6
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

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.
Varun Khandavalli - PeerSpot reviewer
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

"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 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."
"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 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."
"The ingestion engines were pretty good."
 

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."
"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."
"On the tool's online discussion forums, you may get stuck with an issue, making it an area where 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."
"Spring Cloud Data Flow is not an easy-to-use tool, so improvements are required."
"The application has a difficult-to-use parsing capability, which requires a lot of reengineering when the use case isn't specifically met."
"While functional during ingestion workflows, the automation toolkit required manual processes."
 

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."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
24%
Computer Software Company
15%
Retailer
8%
Manufacturing Company
5%
No data available
 

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: October 2025.
869,760 professionals have used our research since 2012.