Dataflow documentation

Dataflow is a managed service for executing a wide variety of data processing patterns. The documentation on this site shows you how to deploy your batch and streaming data processing pipelines using Dataflow, including directions for using service features.

The Apache Beam SDK is an open source programming model that enables you to develop both batch and streaming pipelines. You create your pipelines with an Apache Beam program and then run them on the Dataflow service. TheApache Beam documentation provides in-depth conceptual information and reference material for the Apache Beam programming model, SDKs, and other runners.

To learn basic Apache Beam concepts, see the Tour of Beam andBeam Playground. The Dataflow Cookbook repository also provides ready-to-launch and self-contained pipelines and the most common Dataflow use cases.

Apache, Apache Beam, Beam, the Beam logo, and the Beam firefly mascot are registered trademarks of The Apache Software Foundation in the United States and/or other countries.

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Run HPC highly parallel workloads

With Dataflow, you can run your highly parallel workloads in a single pipeline, improving efficiency and making your workflow easier to manage.

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Run inference with Dataflow ML

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MLStreaming

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Use cases

Create an ecommerce streaming pipeline

Build an end-to-end ecommerce sample application that streams data from a webstore to BigQuery and Bigtable. The sample application illustrates common use cases and best practices for implementing streaming data analytics and real-time artificial intelligence (AI).

ecommerceStreaming

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Except as otherwise noted, the content of this page is licensed under theCreative Commons Attribution 4.0 License, and code samples are licensed under theApache 2.0 License. For details, see theGoogle Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2026-02-18 UTC.