# opendatadiscovery/odd-platform

First open-source data discovery and observability platform. We make a life for data practitioners easy so you can focus on your business.

Repository: https://github.com/opendatadiscovery/odd-platform
Canonical: https://ross.abutalabs.com/products/odd-platform
Homepage: https://opendatadiscovery.org
Language: Java
License: Apache-2.0
License Family: permissive
Topics: oss, data-platform, metadata, metadata-management, data-pipelines, data-engineering, observability, data-catalog, datacatalog, data-discovery, data-lineage, bigdata, alerting, lineage, data-profiling, data-exploration, data-governance, data-quality, data-science, data-observability
Last push: 2026-07-08T09:16:25+00:00

## Health v2 (maintenance only)
Score: 92/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 91, release rhythm 90, longevity 100
- inputs: {"age_days": 1883, "days_push": 56, "days_rel": 68, "gap_med": 13, "n_releases_24m": 12}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1425, forks 144 (observed 2026-08-28T04:04:41.549768+00:00)

## What it is
ODD Platform is an open-source data discovery and observability platform that provides a federated data catalog, end-to-end data and microservices lineage, data quality integration, and alerting. It is the reference implementation of the Open Data Discovery specification and is aimed at data teams of any size.

## Use cases
- find and catalog datasets across the company
- track end-to-end data lineage from ingestion to dashboards
- monitor data pipelines and get alerts on data incidents
- manage data quality checks and governance tags
- catalog ML experiment metadata and lineage
- self-host an open-source data catalog
- deprecate outdated data assets responsibly

## When to choose
- you need an open-source alternative to commercial data catalogs like Collibra or Alation
- your data team wants discovery, lineage, quality, and alerting in one self-hosted tool
- you practice data mesh or need federated metadata management
- you want ML experiment metadata treated as first-class catalog entities

## When to avoid
- you only need lightweight documentation of datasets without a running platform
- you require a fully managed SaaS with no infrastructure to operate
- your stack has no collectors or integrations for the ODD specification

## Facets
- artifact type: application
- maturity: active
- function: search-engine, monitoring, alerting, data-visualization, analytics, self-hosted
- domain: big-data, data-science, analytics, databases
- platform: self-hosted, jvm
- tags: data-catalog, data-observability, data-lineage, data-governance, data-quality, metadata-management, data-discovery, data-profiling, ml-experiments, data-engineering, docker, kubernetes, web-server

## Member repositories
- opendatadiscovery/odd-platform (main) score 92

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:41.549768+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 2026-08-30T04:37:31.873458+00:00, confidence not recorded.
  - readme: https://github.com/opendatadiscovery/odd-platform (fetched 2026-08-28T04:04:41.549768+00:00, sha b4241d5c6de1)
  - homepage: https://opendatadiscovery.org (fetched 2026-08-29T11:49:24.198563+00:00, sha 0c05c875b30c)
  - site_page: https://docs.opendatadiscovery.org/ (fetched 2026-08-29T11:49:24.207723+00:00, sha 14bbb0835f23)
- Data as of 2026-08-30T08:39:29.467469+00:00.