Today, the Flink PMC is proud to announce the official release of Apache Flink 2.0.0! This marks the first release in the Flink 2.x series and is the first major release since Flink 1.0 launched nine years ago. This version is the culmination of two years of meticulous preparation and collaboration, signifying a new chapter in the evolution of Flink.
In this release, 165 contributors have come together to complete 25 FLIPs (Flink Improvement Proposals) and 369 issues.

Flink is an open-source stream processing framework for building real-time data applications, offering powerful features for data processing, analytics, and event-driven architectures. Developers can learn about stream processing concepts, event-driven architectures, and real-time analytics techniques to build scalable and fault-tolerant data pipelines for processing large volumes of data in real-time.

Flink

Apache Flink 2.0.0 marks a significant release in the Flink series, introducing new features and architectural enhancements for real-time data processing. Key highlights include Disaggregated State Management, Materialized Tables, and deep integration with Apache Paimon for streaming lakehouse architectures. The release focuses on improving performance, scalability, and resource efficiency, making real-time computing more accessible and practical for diverse use cases. It also includes a new DataStream V2 API and removes several deprecated APIs, resulting in backward-incompatible changes.

Apache Flink 2.0.0: A new Era of Real-Time Data Processing

List of breaking change programming APIs #