Exactly-once state consistency
Event-time processing
Sophisticated late data handling
SQL on Stream & Batch Data
DataStream API
ProcessFunction (Time & State)
Flexible deployment
High-availability setup
Savepoints
Scale-out architecture
Support for very large state
Incremental Checkpoints
Low latency
High throughput
In-Memory computing
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.
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.
Extract-transform-load (ETL) is a common approach to convert and move data between storage systems.
