Apache Flink®
Stateful Computations over Data Streams
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.
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Flink Capabilities
Operational focus
Flexible deployment
High-availability setup
Savepoints
Layered APIs
SQL on Stream & Batch Data
DataStream API & DataSet API
ProcessFunction (Time & State)
Correctness guarantees
Exactly-once state consistency
Event-time processing
Sophisticated late data handling
Performance
Low latency
High throughput
In-Memory computing
Scalability
Scale-out architecture
Support for very large state
Incremental Checkpoints
Use Cases
Data Pipelines & ETL
Extract-transform-load (ETL) is a common approach to convert and move data between storage systems.
Stream & Batch Analytics
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.
Event Driven Applications
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.