Spring Boot vs. Spring Cloud Data Flow vs. Spring Framework vs. Spring.new Comparison Chart

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.

Spring is a powerful AI-driven platform that allows users to create custom business applications in just minutes. By utilizing natural language processing, Spring transforms your ideas into tailored apps without the need for traditional coding. The platform integrates seamlessly with over 200 tools, including Google Workspace, Slack, GitHub, Salesforce, and many others, ensuring that users can easily build applications on top of their existing workflows. Whether you need a CRM, project management tool, or specialized SaaS product, Spring’s simple interface and robust integrations allow for quick deployment, enhancing both productivity and efficiency.