Airflow
Platform to author, schedule, and monitor workflows
The Lens
Airflow is the industry standard for scheduling and running data pipelines: pulling data from APIs, transforming it, loading it into warehouses, sending reports. Basically cron jobs with a brain: a web UI that shows you every pipeline, every run, what succeeded, what failed, and why.
What's free: Everything. Apache 2.0 license, fully open source, no premium features gated behind a paywall. The entire platform is yours.
Airflow powers data pipelines at Airbnb (where it was created), Lyft, Twitter, and thousands of other companies. The DAG model (directed acyclic graph, basically a flowchart of tasks) is proven. The plugin ecosystem is massive. If a data source exists, someone's written an Airflow connector for it.
The catch: Airflow is complex. Self-hosting means managing a web server, scheduler, workers, a metadata database, and message queue. A production deployment is not a weekend project. The Python-based DAG definitions are powerful but have a steep learning curve. And the scheduler can be resource-hungry. Plan for 4GB+ RAM minimum for anything beyond toy pipelines.
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Free vs Self-Hosted vs Paid
fully free### What's Free Everything. Apache 2.0 license. No open-core tricks, no enterprise edition, no gated features. Every Airflow feature ever built is in the open source release.
### Self-Hosting Cost This is where it gets real: - **Minimum viable**: Single-node Docker Compose on a $20-40/mo VPS (4GB RAM, 2 vCPU). Good for development and small pipelines. - **Production**: Kubernetes deployment with CeleryExecutor. Budget $100-300/mo on cloud infrastructure depending on pipeline volume. - **Serious scale**: Managed Kubernetes + separate Postgres + Redis. $500+/mo easily.
### Managed Alternatives (Pay to Skip Ops) - **Astronomer**: Managed Airflow. Starts ~$300/mo, production tiers $1,000+/mo. - **Google Cloud Composer**: Managed Airflow on GCP. ~$300-400/mo minimum. - **Amazon MWAA**: Managed Airflow on AWS. ~$250-350/mo minimum.
### The Math Self-hosting saves $200-900/mo vs managed services but costs 8-16 hours/month in ops time. At $75/hr, that's $600-1,200 in labor. Managed makes financial sense for most teams unless you already have Kubernetes expertise in-house.
### When to Pay Pay for managed when: your team doesn't have a dedicated platform engineer, uptime matters, or you're running 50+ DAGs. Self-host when: you have Kubernetes expertise, cost is the primary constraint, or you need custom configurations the managed services don't support.
100% free software. The real cost is infrastructure ($20-500+/mo) and ops time -- or $300+/mo for managed services that eliminate both.
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