Astronomer
Managed Apache Airflow service for orchestrating and monitoring data pipelines in the cloud
Open-Source Projects
Discover top open-source software, updated regularly with real-world adoption signals.
Discover top open-source software, updated regularly with real-world adoption signals.
Build modern data pipelines locally with visual, modular code
Self-hosted development environment for creating production-grade ETL/ELT pipelines using Python, SQL, or R in a fast, notebook-style interface with scheduling and debugging.
Mage OSS is a self-hosted development environment that empowers data engineers and analysts to build production-ready data pipelines on their local machines. Designed for teams who need full control over their ETL/ELT workflows, Mage combines the flexibility of modular code with the clarity of a visual, notebook-style interface.
Write pipeline logic in Python, SQL, or R using an interactive editor that supports block-by-block development. Connect to databases, APIs, and cloud storage through prebuilt integrations, then schedule jobs with cron or trigger them manually. Visual debugging tools provide step-by-step logs, live data previews, and transparent error handling. Native dbt support lets you develop and run transformation models directly within the platform.
Install via Docker, pip, or conda—no cloud account required. Ideal for data engineers building local ETL workflows, analytics teams prototyping transformations, and organizations requiring on-premises pipeline orchestration. When teams need enterprise features like AI-assisted development, multi-environment orchestration, or role-based access control, Mage Pro extends the core platform with production-scale capabilities.
When teams consider Mage OSS, these hosted platforms usually appear on the same shortlist.
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Local dbt Model Development
Develop, test, and run dbt transformation models in a notebook-style interface before deploying to production environments.
API-to-Database Integration
Connect to REST APIs, transform JSON responses with Python, and persist results to PostgreSQL or cloud storage with full transparency.
Mage OSS supports Python, SQL, and R for building pipeline logic in a modular, block-based interface.
Yes. Mage OSS is self-hosted and runs locally via Docker, pip, or conda with no mandatory cloud dependencies.
Yes. You can build and run dbt models directly inside Mage OSS using the integrated notebook interface.
Mage OSS is a local development environment for building pipelines. Mage Pro adds AI-assisted development, multi-environment orchestration, RBAC, monitoring, and enterprise features.
Mage OSS supports cron-based scheduling and manual triggers for running pipelines on demand or at specified intervals.
Project at a glance
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