Apache Flink® — Stateful Computations over Data Streams
- Event-driven Applications
- Stream & Batch Analytics
- Data Pipelines & ETL
- Exactly-once state consistency
- Event-time processing
- Sophisticated late data handling
- SQL on Stream & Batch Data
- DataStream API & DataSet API
- ProcessFunction (Time & State)
- Flexible deployment
- High-availability setup
- Savepoints
- Scale-out architecture
- Support for very large state
- Incremental checkpointing
- Low latency
- High throughput
- In-Memory computing
- Apache Flink 1.16.1 Release Announcement
- The Apache Flink Community is pleased to announce a bug fix release for Flink 1.16.
- Delegation Token Framework: Obtain, Distribute and Use Temporary Credentials Automatically
The Apache Flink Community is pleased to announce that the upcoming minor version of Flink (1.17) includes the Delegation Token Framework proposed in FLIP-272. This enables Flink to authenticate to external services at a central location (JobManager) and distribute authentication tokens to the TaskManagers.
- Apache Flink Table Store 0.3.0 Release Announcement
- The Apache Flink Community is pleased to announce the release for Flink Table Store 0.3.0!
- Apache Flink Kubernetes Operator 1.3.1 Release Announcement
The Apache Flink Community is pleased to announce the first bug fix release of the Flink Kubernetes Operator 1.3 series.
- Apache Flink Kubernetes Operator 1.3.0 Release Announcement
The Flink community is happy to announce that the latest Flink Kubernetes Operator version went live today. Beyond the regular operator improvements and fixes the 1.3.0 version also integrates better with some popular infrastructure management tools like OLM and Argo CD. These improvements are clear indicators that the original intentions of the Flink community, namely to provide the de facto standard solution for managing Flink applications on Kubernetes is making steady progress to becoming a reality.