Apache Flink is a powerful open-source framework designed for distributed stream processing. It enables the implementation of both stateful and stateless applications that can handle continuous streams of data. Flink is particularly well-suited for processing large-scale data in real-time, making it a popular choice for applications that require low-latency and high-throughput data processing ¹⁵.

One of the key features of Flink is its ability to provide exactly-once processing semantics, ensuring that each event is processed without duplication, even in the event of failures. This is achieved through mechanisms like periodic and asynchronous checkpointing, which saves the internal state to persistent storage ²⁵. Flink also supports a variety of data sources and sinks, including Apache Kafka, HDFS, and Amazon Kinesis, allowing for flexible integration into existing data ecosystems ²⁵.

Flink’s architecture is built around a data-flow model, where applications are represented as directed acyclic graphs (DAGs) that can be executed in parallel across a cluster of machines ⁵. This scalability and fault tolerance make it a robust choice for modern data processing needs.