CoffeeScript vs. JavaScript vs. Spring Cloud Data Flow vs. Spring Framework Comparison Chart

Underneath that awkward Java-esque patina, JavaScript has always had a gorgeous heart. CoffeeScript is an attempt to expose the good parts of JavaScript in a simple way. The golden rule of CoffeeScript is: “It’s just JavaScript.” The code compiles one-to-one into the equivalent JS, and there is no interpretation at runtime. You can use any existing JavaScript library seamlessly from CoffeeScript (and vice-versa). The compiled output is readable, pretty printed, and tends to run as fast or faster than the equivalent handwritten JavaScript. Most modern JavaScript features that CoffeeScript supports can run natively in Node 7.6+, meaning that Node can run CoffeeScript’s output without any further processing required. This list may be incomplete, and excludes versions of Node that support newer features behind flags; please refer to node.green for full details. You can run the tests in your browser to see what your browser supports.

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.