Apache Airflow is an open-source workflow management tool designed for ETL/ELT (extract, transform, load/extract, load, transform) workflows. It enables users to define, schedule, and monitor complex workflows, with the ability to execute tasks in parallel and handle dependencies between tasks.
I have used it for different workflows, from the simplest to complex and scalable, and in both cases it has many advantages and also details to take care of.
Apache Airflow has a modular architecture, making it easy to add new operators and integrations with external systems. Additionally, it provides a web-based UI for visualizing and monitoring workflow execution. It also includes a rich set of APIs and command-line tools for managing workflows programmatically.
One key benefit of Apache Airflow is its ability to handle complex workflows with ease. This includes workflows involving multiple data sources, transformations, and destinations. Additionally, it provides a robust scheduling engine that can handle failures and retries, ensuring that workflows are completed reliably and on time.
Apache Airflow 2.0 is the latest version and I invite you to review its official documentation. This new version brings many improvements and new features that make the tool even more powerful and user-friendly…
