Apache Flink® is an open source distributed data stream processor. Flink provides efficient, fast, consistent, and robust handling of massive streams of events, as well as batch processing as a special case of stream processing. data Artisans engineers wrote the first line of what would later become Apache Flink® in 2010. We are 100% dedicated in pushing Flink forward as members of the open source community.
Implement robust continuous applications that never stop for immediate insights from your data.
Write latency-critical applications with millisecond responses.
Flink can handle millions of events per second in moderate-sized and scale to 1000s of nodes.
Flink is highly available and fault tolerant; the results of your computation will be correct after failures.
Correct Stream Handling
Flink embraces the notion of event time, guaranteeing that out of order events are handled correctly.
Flink has full batch processing capabilities by treating batch as a special case of streaming.
APIs and Libraries
Choose Flink’s own DataStream, DataSet, SQL, CEP, Gelly, and FlinkML APIs, or use compatibility layers for MapReduce, Storm, Cascading, and Beam.
Batteries included; Flink comes with support for Kafka, HDFS, HBase, Kinesis, S3, RabbitMQ, Elastic, Cassandra, DC/OS, Mesos and YARN.
With over 190 contributors and an impressive list of users, Flink is one of the most active Big Data projects in the ASF.