Code::Blocks vs. JetBrains Fleet vs. MicroPython vs. Spring Cloud Data Flow Comparison Chart

Built from scratch, based on 20 years of experience developing IDEs. JetBrains Fleet uses the IntelliJ code-processing engine, with a distributed IDE architecture and a reimagined UI. We built Fleet to be a fast and lightweight text editor for when you need to quickly browse and edit your code. It starts up in an instant so you can begin working immediately, and it can easily transform into an IDE, with the IntelliJ code-processing engine running separately from the editor itself. Fleet inherits the things that developers love the most from IntelliJ-based IDEs – project and context aware code completion, navigation to definitions and usages, on-the-fly code quality checks, and quick-fixes. Fleet’s architecture is designed to support a range of configurations and workflows. You can simply run Fleet just on your machine, or move some of the processes elsewhere – for example by locating the code processing in the cloud.

Microservice-based streaming and batch data processing for Cloud Foundry and Kubernetes. Spring Cloud Data Flow provides tools to create complex topologies for streaming and batch data pipelines. The data pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. Spring Cloud Data Flow supports a range of data processing use cases, from ETL to import/export, event streaming, and predictive analytics. The Spring Cloud Data Flow server uses Spring Cloud Deployer, to deploy data pipelines made of Spring Cloud Stream or Spring Cloud Task applications onto modern platforms such as Cloud Foundry and Kubernetes. A selection of pre-built stream and task/batch starter apps for various data integration and processing scenarios facilitate learning and experimentation. Custom stream and task applications, targeting different middleware or data services, can be built using the familiar Spring Boot style programming model.