Apache Flink is an open-source, unified stream-processing and batch-processing framework developed by the Apache Software Foundation. It is a distributed processing engine for stateful computations over unbounded and bounded data streams. The core of Apache Flink is a distributed streaming data-flow engine written in Java and Scala, which executes arbitrary dataflow programs in a data-parallel and pipelined manner. Flinks pipelined runtime system enables the execution of bulk/batch and stream processing programs.

Some key features of Apache Flink include:

• Exactly-once consistency guarantees: Flink offers advanced state management with exactly-once consistency guarantees, event-time processing semantics with sophisticated out-of-order and late data handling.

• Unified programming interface: Flink offers a unified programming interface for both stream and batch processing.

• Scalability: Flink is designed to run stateful streaming applications at any scale. Applications are parallelized into possibly thousands of tasks that are distributed and concurrently executed in a cluster.

• Resource management: Flink integrates with all common cluster resource managers such as Hadoop YARN, Apache Mesos, and Kubernetes but can also be set up to run as a stand-alone cluster.

Apache Flink is used to build many different types of streaming and batch applications, due to its broad set of features. Some common types of applications powered by Apache Flink are event-driven applications, stream and batch analytics, data pipelines, and ETL. Flink provides a rich set of connectors to various storage systems such as Kafka, Kinesis, Elasticsearch, and JDBC database systems. Flink has been proven to scale to thousands of cores and terabytes of application state, delivering high throughput and low latency, and powering some of the world’s most demanding stream processing applications.