Airflow

Airflow is an open-source platform for developing, scheduling, and orchestrating complex data workflows. Originally built by Airbnb and now a top-level Apache project, it allows users to author pipelines as directed acyclic graphs (DAGs) written in Python. The system provides a robust scheduler, a dynamic workflow engine, and extensive monitoring capabilities for data engineering operations. Key features include Python-native workflow definition, a rich library of prebuilt operators for databases, cloud services, and big data technologies, and a flexible scheduler supporting complex dependencies and time-based triggers. The web UI offers visualization, monitoring, and task management. Airflow supports horizontal scaling, dynamic DAG generation, and integrates with popular tools such as Apache Spark, AWS S3, Google BigQuery, Snowflake, and Kubernetes. It also provides retry mechanisms, alerting, and detailed execution logs. Airflow is built for data engineers, data scientists, and analytics teams who manage ETL, ELT, and data pipeline workloads. It suits organizations ranging from startups to enterprises that need reliable, scalable, and maintainable workflow orchestration. It is ideal for teams already working in Python or those building data platforms that require reproducibility and version control over their pipelines. Airflow is free and open-source under the Apache 2.0 license. There are no licensing fees