# apache/griffin

Mirror of Apache griffin

Repository: https://github.com/apache/griffin
Canonical: https://ross.abutalabs.com/products/griffin
Language: Scala
License: Apache-2.0
License Family: permissive
Topics: griffin
Archived: true
Last push: 2025-08-03T00:07:35+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 34, release rhythm 35, longevity 100
- inputs: {"age_days": 3486, "days_push": 396, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1172, forks 585 (observed 2026-08-28T04:03:51.712821+00:00)

## What it is
Apache Griffin is a model-driven data quality service platform for defining, executing, and reporting data quality measures across multiple data systems. It provides a standard process for on-demand examination of data quality in big data environments.

## Use cases
- measure data quality across hadoop and spark pipelines
- define and schedule data quality checks for big data
- validate data accuracy and completeness before feeding machine learning models
- monitor data quality for IoT sensor data
- generate data quality reports across multiple data systems

## When to choose
- you need a standardized, model-driven data quality framework for big data platforms
- you want on-demand data quality measurement with defined measures, executions, and reports
- your organization runs Spark/Hadoop ecosystems and needs cross-system DQ validation

## When to avoid
- you need lightweight data validation in a small application rather than a platform
- your stack does not involve big data systems like Spark or Hadoop
- you need actively evolving features - the project appears to be in maintenance mode

## Facets
- artifact type: service
- maturity: maintenance
- function: monitoring, analytics, etl, data-science
- domain: big-data, analytics, databases
- platform: jvm, self-hosted, cloud
- tags: data-quality, apache, scala, spark, model-driven, data-engineering, docker

## Member repositories
- apache/griffin (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:51.712821+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 2026-08-30T06:28:25.944451+00:00, confidence not recorded.
  - readme: https://github.com/apache/griffin (fetched 2026-08-28T04:03:51.712821+00:00, sha f0330d2d7d85)
- Data as of 2026-08-30T08:39:29.467469+00:00.