StreamSets vs Cloudflow: What are the differences?

Developers describe StreamSets as "Where DevOps Meets Data Integration". The industry's first data operations platform for full life-cycle management of data in motion. On the other hand, Cloudflow is detailed as "*Streaming Data Pipeline on Kubernetes *". It enables you to quickly develop, orchestrate, and operate distributed streaming applications on Kubernetes. With Cloudflow, streaming applications are comprised of small composable components wired together with schema-based contracts. It can dramatically accelerate streaming application development—​reducing the time required to create, package, and deploy—​from weeks to hours.

StreamSets belongs to "Message Queue" category of the tech stack, while Cloudflow can be primarily classified under "Big Data Tools".

Some of the features offered by StreamSets are:

• Build Batch & Streaming Pipelines in Hours
• Map and Monitor Runtime Performance
• Protect Sensitive Data as it Arrives

On the other hand, Cloudflow provides the following key features:

• Apache Spark, Apache Flink, and Akka Streams
• Focus only on business logic, leave the boilerplate to us
• We provide all the tooling for going from business logic to a deployable Docker image

Cloudflow is an open source tool with 172 GitHub stars and 50 GitHub forks. Here's a link to Cloudflow's open source repository on GitHub.