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Why Apache Flink®

Apache Flink is an open source stream processing platform for real-time analytics and real-time applications. Apache Flink provides efficient, fast, accurate, and fault tolerant handling of massive streams of events. Apache Flink also supports 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. data Artisans is 100% dedicated to pushing Apache Flink forward as members of the open source community.

In this high-level overview of Apache Flink, we’ll highlight a selection of Apache Flink’s key features and will provide links to additional resources for more detail.

If you’re new to stream processing and would like to learn more, we recommend starting with our downloadable report, “Stream Processing for Real-Time Businesses, Powered by Apache Flink”.

Benefits

Streaming Processing

Apache Flink provides true event-at-a-time stream processing, enabling 24/7, continuous applications for immediate insights and actions on your data.

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Low Latency, High Throughput

Apache Flink processes millions of events per second in real-time and powers stream processing applications on 1000s of nodes in production.

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Fault Tolerance

Apache Flink provides highly available and fault tolerant stream processing; Flink supports exactly once semantics even in the event of failure.

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Savepoints for Versioning

Apache Flink's savepoints make it possible for a user to fix issues, reprocess data, update code, and manage upgrades easily and with data consistency.

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Event Time Handling

Apache Flink embraces the notion of event time in stream processing, guaranteeing that out of order events are handled correctly and that results are accurate.

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Re-scalable Application State

Apache Flink's application state is rescalable, making it possible to add more resources while maintaining exactly once semantics in the application.

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Streaming SQL

Apache Flink offers a streaming SQL API, making it accessible for business and non-technical users to harness the power of stream processing.

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Complex Event Processing

Apache Flink's complex event processing (CEP) library makes it possible to detect and respond to mission-critical business events in real-time.

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Expressive Streaming APIs

Apache Flink's stream processing APIs make it easy to model complex, real-world business problems by exposing key building blocks to developers.

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Batch Processing

Apache Flink has full batch processing capabilities, where batch is a special case of stream processing. Flink offers a unified data processing framework.

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Runs Everywhere

Apache Flink supports the stream processing ecosystem, including Kafka, HDFS, Kinesis, Cassandra, DC/OS, Mesos, Docker, Kubernetes, and YARN.

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Open Source Community

Apache Flink has 330+ contributors and a long list of production users; it is one of the most active stream processing and big data projects in ASF.

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Apache Flink Resources to Get You Started

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