Codehooks vs. NestJS vs. Oracle NoSQL Database vs. Spring Cloud Data Flow Comparison Chart

Gives you true flexibility by allowing use of any other libraries thanks to modular architecture. An adaptable ecosystem that is a fully-fledged backbone for all kinds of server-side applications. Takes advantage of latest JavaScript features, bringing design patterns and mature solutions to Node.js world. A complete development kit for building scalable server-side apps. In recent years, thanks to Node.js, JavaScript has become the “lingua franca” of the web for both front and backend applications. This has given rise to awesome projects like Angular, React and Vue, which improve developer productivity and enable the creation of fast, testable, and extensible frontend applications. However, while plenty of superb libraries, helpers, and tools exist for Node (and server-side JavaScript), none of them effectively solve the main problem of - Architecture.

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.