Apache Flink
Stateful computations over data streams for real-time analytics.
Apache Flink is a distributed stream and batch processing framework for stateful computations over bounded and unbounded data streams. It runs user-supplied code across a cluster of machines and is designed to execute in common cluster environments, supporting event-driven applications, stream and batch analytics, and data pipelines and ETL. It provides exactly-once state consistency, event-time processing, late data handling, low latency, and high throughput.
Its layered APIs include SQL on stream and batch data, the DataStream API, and ProcessFunction for time and state. Operational features include flexible deployment, high-availability setup, savepoints, incremental checkpoints, and support for very large state. Related components include the Kubernetes Operator for deploying Flink on Kubernetes, Flink CDC, Flink Agents, Flink ML, and Stateful Functions. Security relies on network-level controls, with SSL/TLS, REST API authentication, and SQL Gateway authentication available but disabled by default; the Kubernetes Operator uses Kubernetes RBAC for access control.
Flink is intended for data engineers and platform teams building streaming and batch workloads on cluster infrastructure. It is distributed under the Apache License and available for download, with stable and long-term support releases documented alongside snapshot versions.
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