Ross ROSS = Recommend OSS · open-source software intelligence for agents

mage-ai/mage-ai

🧙 Build, run, and manage data pipelines for integrating and transforming data. observed · 2026-08-28

github.com/mage-ai/mage-ai · homepage · Python · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

78/100

  • Activity 97
  • Release rhythm 42
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 115
  • age_days: 1570
  • days_rel: 224
  • days_push: 20
  • n_releases_24m: 6

Full methodology

Adoption not part of the score

8814 stars · 990 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Mage OSS is a self-hosted data pipeline tool for building, running, and orchestrating ETL/ELT workflows in a notebook-style UI using Python, SQL, or R. It includes prebuilt connectors, cron scheduling, visual debugging, and integrations with Spark and dbt, with a commercial Mage Pro tier for enterprise scale.

Use cases

  • build etl pipelines with python and sql
  • schedule data pipeline jobs with cron
  • orchestrate data transformations between databases and warehouses
  • self-hosted airflow alternative for data pipelines
  • integrate stripe salesforce and bigquery data
  • run dbt and spark jobs in a visual pipeline tool
  • debug data pipelines with live previews and logs

When to choose

  • you want a notebook-style visual UI for building modular data pipelines
  • you need self-hosted orchestration with scheduling, retries, and backfills
  • your team works in Python, SQL, or R and wants prebuilt data connectors

When to avoid

  • you need only lightweight cron scheduling without a pipeline UI
  • you require enterprise features like RBAC and multi-tenant workspaces, which are in the paid Mage Pro tier
  • your pipelines are purely streaming with sub-second latency requirements

Facets

application · maturity active

etl workflow-automation scheduling data-science monitoring developer-tools analytics self-hosted developer-tools python self-hosted cross-platform data-pipelines orchestration elt reverse-etl notebook-ui dbt spark data-integration airflow-alternative data-engineering automation docker web-server

6 sources

Member repositories

RepositoryRoleHealth v2
mage-ai/mage-aimain78

For agents

markdown · JSON · MCP: product_card(name="mage-ai/mage-ai")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem