Spring Cloud Data Flow Overview

Spring Cloud Data Flow is the #7 ranked solution in our list of Streaming Analytics tools. It is most often compared to Apache Flink: Spring Cloud Data Flow vs Apache Flink

What is Spring Cloud Data Flow?

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.

Buyer's Guide

Download the Data Integration Tools Buyer's Guide including reviews and more. Updated: July 2021

Spring Cloud Data Flow Video

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Ken Ramirez
Senior Digital Architect at Kubota USA Inc.
Consultant
Gives us the simplicity of using off-the-shelf data flow plug-in components

What is our primary use case?

The organization I’m currently consulting for is performing a lift-and-shift, moving its existing software from an on-prem platform and infrastructure to the cloud. They have chosen Azure as their cloud provider. As part of this process, they have orders to move away from expensive, monolithic, proprietary software platforms, and to replace them with open-source, publicly available software technologies. One area we’ll be replacing is their current middleware software which consists of IBM WebSphere Message Broker. While it is a fine tool for the most part, it’s also bulky and expensive to… more »

What other advice do I have?

I would rate this product (or set of technologies) a solid eight out of 10. The things that would keep me from giving it a full 10 are the fact that the graphic user interface portion of the toolset still needs some polishing and performs somewhat slowly. However, I have not had an opportunity to run this tool set on higher performing machines, and have been limited to simply running it within a set of virtual machines on my own workstation.