Apache Airflow is an open-source software platform that helps in programmatically authoring, scheduling, and monitoring workflows. It provides a way to express dependencies between tasks and execute them in an organized fashion. As a result, users can focus on the logic of their pipelines rather than worrying about the infrastructure details.


The name "Airflow" refers to the concept of data flow and how data moves through a system. In Apache Airflow, this data flow is represented by directed acyclic graphs (DAGs), which define the tasks and their dependencies.


One of the key features of Apache Airflow is its extensibility. It comes with a rich set of operators and sensors that can be used out of the box, but users can also extend it to their own needs by building custom operators, sensors, hooks, and executors.


Apache Airflow has gained popularity in recent years due to its flexibility and ease of use. It is used by organizations of all sizes to build and manage their data pipelines, including Airbnb, Lyft, and PayPal. Because it is open source, users can benefit from the large and active community of contributors who are constantly improving the platform.


In summary, Apache Airflow is a powerful tool for building and managing data workflows. Its flexibility and extensibility make it a popular choice for organizations that need to process and analyze large amounts of data.