![]() Is the go-to resource for information about implementing and customizingĪirflow, as well as for help troubleshooting problems.Īnd because Airflow is open-source software, organizations don't have toīuild, support, and maintain it themselves. TheĬommunity provides a wealth of resources - such as reliable, up-to-date Airflow documentation and use-case-specific Airflow tutorials, in addition to discussion forums, a dev mailing list, and an active Airflow Slack channel - to support novice and experienced users alike. Monitoring, providing at-a-glance insights into the performance andĪirflow has a large community of engaged maintainers, committers, andĬontributors who help to steer, improve, and support the platform. This makes the production dataflows that power your criticalĪirflow's web-based UI simplifies task management, scheduling, and Test and validate your data pipelines before deploying them to Treating data pipelines as code lets you create CI/CD processes that ![]() Need to write and maintain custom code, and accelerating pipeline ![]() Pre-built Python functions that automate common tasks - that users canĬombine like building blocks to design complex workflows, reducing the Near-real-time, low-latency applications.Īirflow simplifies data pipeline development, allowing users to define Traditional batch data processing use cases, as well as for demanding This flexibility enables it to be used for Massive deployments, with thousands of concurrent users, and tens of Small deployments - with just a few users and data pipelines - to Own custom operators, hooks, and sensors. Airflow’s simple and flexible pluginĪrchitecture allows users to extend its functionality by writing their Jobs, coordinates dependencies between tasks, and gives organizations aĬentral point of control for monitoring and managing workflows.Īirflow provides many benefits, including: Flexibility, Extensibility, and ScalabilityĪirflow is Python-based, so it supports all of the libraries,įrameworks, and modules available for Python, and benefits from the hugeĮxisting base of Python users. Workflows - like the data pipelines that crisscross cloud andĪirflow provides the workflow management capabilities that are integral Apache Airflow is especially useful for creating and managing complex
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