Apache Airflow

Apache Airflow: A Platform for Programmatically Authoring, Scheduling, and Monitoring Workflows

Apache Airflow is an open-source platform designed to help organizations programmatically author, schedule, and monitor workflows. With a wide range of users across 500+ organizations, Airflow has become a popular choice for managing complex workflows. Whether you're working with data, processing tasks, or monitoring progress, Airflow provides a rich user interface to visualize pipelines, track progress, and troubleshoot issues.

Main Features:

1. Workflow Management: Airflow allows users to define, schedule, and monitor workflows using Python code.
2. DAGs (Directed Acyclic Graphs): Airflow uses DAGs to represent the sequence of tasks in a workflow, making it easy to visualize and manage dependencies between tasks.
3. Task Scheduling: Airflow provides a robust scheduling system that can handle complex workflows with multiple tasks and dependencies.
4. XCom: Airflow's XCom feature enables tasks to pass metadata to each other, facilitating communication and coordination within workflows.
5. Rich User Interface: The Airflow UI provides a comprehensive view of pipeline execution, allowing users to monitor progress, troubleshoot issues, and visualize data pipelines.

Who Uses Apache Airflow?

Airflow is used by over 500 organizations worldwide, including top companies in the tech industry. If you use Airflow, feel free to make a PR to add your organization to the list!

Who Maintains Apache Airflow?

Apache Airflow is maintained by a community of core committers and maintainers who review and merge pull requests, as well as steer conversations around new feature requests.

What Goes into the Next Release?

Airflow follows the Semver versioning scheme, with MAJOR releases for breaking changes, MINOR releases for new features, and PATCH releases for bug fixes and documentation updates. You can find more information on Airflow Improvement Proposals (AIPs) on the Airflow Wiki.