Glossary>Data Processing & Management>Apache Beam

Apache Beam

Apache Beam is an open-source unified programming model designed for defining and executing data processing workflows, both batch and streaming. It provides a set of APIs in multiple languages to build complex data pipelines that can run on various execution engines like Apache Flink, Apache Spark, and Google Cloud Dataflow.

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About Apache Beam

Apache Beam was created in 2016 by Google as an open-source project to unify their internal data processing models and provide a standard for defining both batch and streaming data pipelines. It evolved from Google's earlier data processing frameworks, MapReduce, Flume, and MillWheel, to offer a more flexible and comprehensive solution for handling large-scale data workflows.

Strengths of Apache Beam include its unified model for batch and stream processing, portability across multiple execution engines, and support for multiple programming languages. Weaknesses include a steeper learning curve and potential performance overhead compared to native solutions. Competitors include Apache Spark, Apache Flink, and Google Cloud Dataflow.