# opendatadiscovery/awesome-data-catalogs

📙 Awesome Data Catalogs and Observability Platforms.

Repository: https://github.com/opendatadiscovery/awesome-data-catalogs
Canonical: https://ross.abutalabs.com/products/awesome-data-catalogs
License: MIT
License Family: permissive
Topics: data-catalog, data-discovery, metadata, dataops, awesome, observability, data-engineering, data-quality, big-data, opensource, open-source, ml, awesome-list, oss, opendata, datadiscovery, metadata-management, datacatalog
Last push: 2025-08-14T14:10:59+00:00

## Health v2 (maintenance only)
Score: 48/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 36, release rhythm 35, longevity 100
- inputs: {"age_days": 1876, "days_push": 384, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1062, forks 81 (observed 2026-08-28T04:03:26.205984+00:00)

## What it is
A curated awesome-list of data catalogs, data discovery, and data observability platforms, spanning open-source, cloud, and proprietary tools. It serves as a reference index for Data & AI governance tooling.

## Use cases
- find open source data catalog tools
- compare data observability platforms
- discover metadata management solutions
- research data governance tooling options
- find alternatives to Collibra or Alation
- learn about data discovery landscape

## When to choose
- you need a broad survey of data catalog and observability tools before choosing one
- you want a maintained, categorized index of open-source and commercial options

## When to avoid
- you need working software rather than a list of links
- you need in-depth benchmarks or comparisons of the tools

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, developer-tools
- domain: big-data, data-science, awesome-lists, analytics
- platform: cross-platform
- tags: awesome-list, data-catalog, data-discovery, metadata-management, data-observability, data-governance, data-quality, curated-list, data-engineering

## Member repositories
- opendatadiscovery/awesome-data-catalogs (main) score 48

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:26.205984+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 2026-08-30T06:56:45.974637+00:00, confidence not recorded.
  - readme: https://github.com/opendatadiscovery/awesome-data-catalogs (fetched 2026-08-28T04:03:26.205984+00:00, sha c384f25922dc)
- Data as of 2026-08-30T08:39:29.467469+00:00.