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MA
Mage AI
CommunityOpen-source data pipeline tool for building, running, and monitoring ETL/ELT workflows with a notebook-style UI.
| Runs | mageai/mageai:0.9.80 |
|---|---|
| Stack | python |
| Provisioned for it | postgres |
| Verified | Not yet |
Why deploy on Railyard
Railyard provisions postgres alongside it automatically — zero-downtime deploys, automatic backups and scaling come from the same platform, on a server you already pay for.
Deploying Mage AI is one piece of a bigger stack you can keep building — add a database, a worker, a cache, or another app, all on the same servers you already pay for.
Good for
- Building ETL/ELT pipelines visually instead of hand-writing Airflow DAGs
- Scheduling and monitoring recurring data-sync jobs
- A notebook-style environment for data transformation code
Good to know
- Postgres is wired up for pipeline/run metadata instead of the default SQLite, so history survives a redeploy
- Projects and pipeline code persist on the mounted volume; set a real DEFAULT_OWNER_EMAIL before going live