{"categories":[{"label":"Monitoring","url":"https://skillfed.io/packages/category/system-monitoring/4"}],"enrichment":{"capability":"Integrates Apache Beam data processing pipelines into Apache Airflow workflows, enabling orchestration of batch and streaming jobs through Airflow's DAG framework.","skillfed_tags":["airflow-provider","beam-integration","workflow-orchestration"],"use_cases":["Schedule and monitor Apache Beam batch jobs as part of a larger Airflow data pipeline.","Orchestrate Beam streaming pipelines with Airflow's scheduling and retry logic.","Integrate Beam processing with other Airflow operators in a unified DAG.","Run Beam jobs on Google Cloud Dataflow through Airflow task dependencies.","Manage dependencies between Beam pipelines and upstream/downstream data tasks."],"what_it_does":"This is an Apache Airflow provider package that bridges Apache Beam into Airflow's workflow orchestration model. It supplies operators and hooks that allow you to define and schedule Beam pipelines as tasks within Airflow DAGs, treating data processing jobs as first-class workflow components. The package depends on apache-airflow, apache-beam, pyarrow, and numpy, and is designed for teams already running Airflow who want to orchestrate Beam workloads without leaving the Airflow ecosystem.\n\nThe package is actively maintained, supports Python 3.10\u20133.13, and requires Apache Airflow >=2.11.0 and Apache Beam >=2.69.0. It carries an Apache-2.0 license and integrates with optional Google Cloud dependencies for Dataflow support. Installation is straightforward via pip, and the package is positioned as a standard extension for Airflow users working with Beam-based data pipelines.","worth_installing":"Yes, if you are already running Apache Airflow and need to orchestrate Apache Beam pipelines. The package is actively maintained, carries no known vulnerabilities, has low install friction, and integrates cleanly with Airflow's task model. Install only if you have both Airflow and Beam in your stack; it adds no value as a standalone library."},"id":"apache-airflow-providers-apache-beam","links":{"html":"https://skillfed.io/packages/apache-airflow-providers-apache-beam","md":"https://skillfed.io/packages/apache-airflow-providers-apache-beam.md","pypi":"https://pypi.org/project/apache-airflow-providers-apache-beam/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-03-02","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"apache-airflow-providers-apache-beam","python_support":"supports_current","summary":"Provider package apache-airflow-providers-apache-beam for Apache Airflow"},"popularity":{"monthly_downloads":287421,"position":8032,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"6.2.3"}