The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies.
Programmatically author, schedule and monitor workflows.
Airflow pipelines are defined in Python, allowing for dynamic pipeline generation. This allows for writing code that instantiates pipelines dynamically.
Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity.
Easily define your own operators and extend libraries to fit the level of abstraction that suits your environment.
Airflow pipelines are lean and explicit. Parametrization is built into its core using the powerful Jinja templating engine.
Monitor, schedule and manage your workflows via a robust and modern web application.