# datahub-project/datahub

The Context Platform for your Data and AI Stack

Repository: https://github.com/datahub-project/datahub
Canonical: https://ross.abutalabs.com/products/datahub
Homepage: https://datahub.com
Language: Python
License: Apache-2.0
License Family: permissive
Topics: metadata, datahub, data-catalog, data-discovery, data-governance, agent-platform, context-management, data-observability
Last push: 2026-08-27T00:10:52+00:00

## Health v2 (maintenance only)
Score: 98/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 97, longevity 100
- inputs: {"age_days": 3941, "days_push": 7, "days_rel": 20, "gap_med": 11, "n_releases_24m": 22}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 12586, forks 3675 (observed 2026-08-28T04:10:59.365799+00:00)

## What it is
DataHub is an open-source data catalog and metadata platform providing data discovery, governance, lineage, and observability across an organization's data and AI stack. It ingests metadata from 150+ integrations and exposes it via UI, APIs, SDKs, and MCP-based context services for AI agents.

## Use cases
- catalog all datasets, dashboards, and ML models in one searchable place
- track column-level data lineage across pipelines
- set up data quality checks and anomaly detection
- assign data ownership and tag PII for governance
- give AI agents trusted metadata context via MCP
- self-host a data catalog on Kubernetes or Docker

## When to choose
- you need an enterprise-grade, self-hosted data catalog with broad connector support
- you want unified discovery, lineage, and observability across a large data estate
- you need programmatic metadata management via APIs and SDKs

## When to avoid
- you only need lightweight documentation of a handful of tables
- you want a simple spreadsheet-style data inventory without infrastructure
- your team cannot operate a multi-service Docker/Kubernetes deployment

## Facets
- artifact type: application
- maturity: active
- function: search-engine, monitoring, etl, api-framework, mcp, analytics
- domain: databases, analytics, data-science, large-language-models, self-hosted, developer-tools
- platform: python, self-hosted, cloud
- tags: data-catalog, metadata-management, data-governance, data-discovery, data-lineage, data-observability, data-quality, context-management, metadata-ingestion, data-contracts, data-engineering, docker, kubernetes, web-server

## Member repositories
- datahub-project/datahub (main) score 98

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:59.365799+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:13:57.039096+00:00, confidence not recorded.
  - readme: https://github.com/datahub-project/datahub (fetched 2026-08-28T04:10:59.365799+00:00, sha 03c117242bb4)
  - homepage: https://datahub.com (fetched 2026-08-29T08:10:35.187028+00:00, sha 3d6a1da2122c)
  - site_page: https://docs.datahub.com/integrations (fetched 2026-08-29T08:10:35.200117+00:00, sha 5d3bf1a52ce4)
  - site_page: https://docs.datahub.com/docs/features (fetched 2026-08-29T08:10:35.202703+00:00, sha 84ed536b40bb)
  - site_page: https://datahub.com/docs (fetched 2026-08-29T08:10:35.208403+00:00, sha 8cf744048dc9)
  - site_page: https://datahub.com/company (fetched 2026-08-29T08:10:35.205986+00:00, sha 31da59676d99)
- Data as of 2026-08-30T08:39:29.467469+00:00.