Apache Airflow is a phenomenal tool for building data flows. It’s reliable, well-maintained, well-documented, and has plugins for just about everything. It’s easy to extend, has pre-built deployment patterns, and is readily available in a variety of cloud environments. However, it’s also an aging tool, and has a few quirks that hearken to an earlier time in its development. Some issues include rigid DAG-centric dataflows, confusing differences between logical runtime and wall-clock execution time, and significant limitations in the size of individual DAGs.