apache/airflow

Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

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What it does

Apache Airflow is a tool that lets data teams build, schedule, and monitor automated workflows — essentially setting up a series of tasks (like collecting data, processing it, and generating reports) to run automatically on a schedule without human intervention. Think of it like a highly sophisticated automation system that keeps your data pipelines running smoothly and alerts you when something goes wrong.

Why it matters for PMs

With over 44,000 stars and 16,500 forks on GitHub, Airflow is one of the most widely adopted tools in the data engineering space, meaning it's likely already running inside companies your product competes with or partners with. For PMs and founders, this signals that automated data workflows are now a baseline expectation — teams that invest in orchestrating their data pipelines ship faster, make better decisions, and waste less engineering time on manual data tasks.

Early Signal Score32

Early stage — limited signal data

Stars
44.3k
Forks
16.5k
Contributors
413
Language
Python

Score updated Feb 18, 2026

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