Apache Beam unifies batch and streaming for big data

Apache Beam, a unified programming model for both batch and streaming data, has graduated from the Apache Incubator to become a top-level Apache project.

Aside from becoming another full-fledged widget in the ever-expanding Apache tool belt of big-data processing software, Beam addresses ease of use and dev-friendly abstraction, rather than simply offering raw speed or a wider array of included processing algorithms.

Beam us up!

Beam provides a single programming model for creating batch and stream processing jobs (the name is a hybrid of “batch” and “stream”), and it offers a layer of abstraction for dispatching to various engines used to run the jobs. The project originated at Google, where it’s currently a service called GCD (Google Cloud Dataflow). Beam uses the same API as GCD, and it can use GCD as an execution engine, along with Apache Spark, Apache Flink (a stream processing engine with a highly memory-efficient design), and now Apache Apex (another stream engine for working closely with Hadoop deployments).

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