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Why Apache Flink®?

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.

Stream Processing

Implement robust continuous applications that never stop for immediate insights from your data.

Low Latency

Write latency-critical applications with millisecond responses.

High Throughput

Flink can handle millions of events per second in moderate-sized and scale to 1000s of nodes.

Fault Tolerant

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.

Batch Processing

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.

Rich Ecosystem

Batteries included; Flink comes with support for Kafka, HDFS, HBase, Kinesis, S3, RabbitMQ, Elastic, Cassandra, DC/OS, Mesos and YARN.

Community

With over 190 contributors and an impressive list of users, Flink is one of the most active Big Data projects in the ASF.