Apache Flink® — Stateful Computations over Data Streams
All streaming use cases
- Event-driven Applications
- Stream & Batch Analytics
- Data Pipelines & ETL
Guaranteed correctness
- Exactly-once state consistency
- Event-time processing
- Sophisticated late data handling
Layered APIs
- SQL on Stream & Batch Data
- DataStream API & DataSet API
- ProcessFunction (Time & State)
Operational Focus
- Flexible deployment
- High-availability setup
- Savepoints
Scales to any use case
- Scale-out architecture
- Support for very large state
- Incremental checkpointing
Excellent Performance
- Low latency
- High throughput
- In-Memory computing
- How to query Pulsar Streams using Apache Flink
- This blog post discusses the new developments and integrations between Apache Flink and Apache Pulsar and showcases how you can leverage Pulsar’s built-in schema to query Pulsar streams in real time using Apache Flink.
- Apache Flink 1.9.1 Released
The Apache Flink community released the first bugfix version of the Apache Flink 1.9 series.
- The State Processor API: How to Read, write and modify the state of Flink applications
- This post explores the State Processor API, introduced with Flink 1.9.0, why this feature is a big step for Flink, what you can use it for, how to use it and explores some future directions that align the feature with Apache Flink's evolution into a system for unified batch and stream processing.
- Apache Flink 1.8.2 Released
The Apache Flink community released the second bugfix version of the Apache Flink 1.8 series.
- Flink Community Update - September'19
- This has been an exciting, fast-paced year for the Apache Flink community. But with over 10k messages across the mailing lists, 3k Jira tickets and 2k pull requests, it is not easy to keep up with the latest state of the project. Plus everything happening around it. With that in mind, we want to bring back regular community updates to the Flink blog.