Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale.
Flexible deployment
High-availability setup
Savepoints
SQL on Stream & Batch Data
DataStream API & DataSet API
ProcessFunction (Time & State)
Exactly-once state consistency
Event-time processing
Sophisticated late data handling
Low latency
High throughput
In-Memory computing
Scale-out architecture
Support for very large state
Incremental Checkpoints
Extract-transform-load (ETL) is a common approach to convert and move data between storage systems.
Analytical jobs extract information and insight from raw data. Apache Flink supports traditional batch queries on bounded data sets and real-time, continuous queries from unbounded, live data streams.
An event-driven application is a stateful application that ingests events from one or more event streams and reacts to incoming events by triggering computations, state updates, or external actions.