JHipster vs. NestJS vs. Spring Cloud Data Flow vs. python-sql Comparison Chart

JHipster is a development platform to quickly generate, develop, and deploy modern web applications and microservice architectures. We support many frontend technologies, including Angular, React, and Vue. We even have mobile app support for Ionic and React Native! On the backend, we support Spring Boot (with Java or Kotlin), Micronaut, Quarkus, Node.js, and . NET. For deployment, we embrace cloud-native principles with Docker and Kubernetes. Deployment support exists for AWS, Azure, Cloud Foundry, Google Cloud Platform, Heroku, and OpenShift. Our goal is to generate a complete and modern web app or microservice architecture. A high-performance and robust server-side stack with excellent test coverage. A sleek, modern, mobile-first UI with Angular, React, or Vue + Bootstrap for CSS. A powerful workflow to build your application with Webpack and Maven or Gradle. Resilient microservice architecture with cloud-native principles in mind.

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.