# dpapathanasiou/simple-graph

This is a simple graph database in SQLite, inspired by "SQLite as a document database"

Repository: https://github.com/dpapathanasiou/simple-graph
Canonical: https://ross.abutalabs.com/products/simple-graph
License: MIT
License Family: permissive
Last push: 2025-02-15T14:49:04+00:00

## Health v2 (maintenance only)
Score: 26/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 6, release rhythm 8, longevity 100
- inputs: {"age_days": 2083, "days_push": 564, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1527, forks 90 (observed 2026-08-28T04:04:58.511627+00:00)

## What it is
A simple graph database implemented on top of SQLite, storing nodes as JSON objects and edges as id pairs with optional properties. It provides CRUD SQL statements and traversal queries via Common Table Expressions, with bindings in multiple languages.

## Use cases
- store a social graph in sqlite
- build an interest graph for recommendations
- manage task lists with dependencies
- track bugs and their relationships
- model CRM contacts and interactions
- run graph traversals without running a graph server

## When to choose
- you want graph storage with zero infrastructure beyond SQLite
- your dataset fits on a single machine and you need simple node/edge CRUD
- you prefer embedding a library over deploying Neo4j or similar

## When to avoid
- you need high-throughput distributed graph processing
- you require advanced graph query languages like Cypher or Gremlin
- you need built-in replication or horizontal scaling

## Facets
- artifact type: library
- maturity: active
- function: database, search-engine
- domain: databases, developer-tools, backend
- platform: python, go, cross-platform, cli
- tags: graph-database, sqlite, embedded-database, graph-traversal

## Member repositories
- dpapathanasiou/simple-graph (main) score 26

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:58.511627+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 2026-08-30T04:31:33.535267+00:00, confidence not recorded.
  - readme: https://github.com/dpapathanasiou/simple-graph (fetched 2026-08-28T04:04:58.511627+00:00, sha b29114ea12aa)
- Data as of 2026-08-30T08:39:29.467469+00:00.