# google/mangle

Repository: https://github.com/google/mangle
Canonical: https://ross.abutalabs.com/products/mangle
Language: Go
License: Apache-2.0
License Family: permissive
Last push: 2026-08-05T19:29:44+00:00

## Health v2 (maintenance only)
Score: 73/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 96, release rhythm 30, longevity 98
- inputs: {"age_days": 1378, "days_push": 28, "days_rel": 305, "gap_med": 163, "n_releases_24m": 2}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2986, forks 154 (observed 2026-08-28T04:07:34.204492+00:00)

## What it is
Mangle is a deductive database programming language implemented as an embeddable Go library. It extends Datalog with aggregation, function calls, and optional type-checking to uniformly query and integrate data from multiple sources.

## Use cases
- query data from multiple sources with a uniform declarative language
- write recursive rules over relational data
- detect vulnerable software dependencies like log4j via logic rules
- embed a Datalog engine into Go applications
- model domain knowledge with machine-readable rules
- build a deductive database gRPC service

## When to avoid
- you need guaranteed termination for all programs, since extensions can lose it
- you need a production-hardened, officially supported database product
- you want a standalone database server rather than an embeddable library
- your team is unfamiliar with logic programming paradigms

## Facets
- artifact type: library
- maturity: active
- function: programming-language, interpreter, database, parser
- domain: databases, programming-languages, artificial-intelligence
- platform: go, cross-platform
- tags: datalog, deductive-database, declarative-language, logic-programming, knowledge-representation, query-language, algorithms

## Member repositories
- google/mangle (main) score 73

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:34.204492+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 2026-08-30T07:31:25.693766+00:00, confidence not recorded.
  - readme: https://github.com/google/mangle (fetched 2026-08-28T04:07:34.204492+00:00, sha 00ef00bdf492)
- Data as of 2026-08-30T08:39:29.467469+00:00.