using-graph-databaseslisted

# Graph Databases ## Purpose This skill guides selection and implementation of graph databases for applications where relationships between entities are first-class citizens. Unlike relational databases that model relationships through foreign keys and joins, graph databases natively represent connections as properties, enabling efficient traversal-heavy queries. ## When to Use This Skill Use graph databases when: - **Deep relationship traversals** (4+ hops): "Friends of friends of friends" - **Variable/evolving relationships**: Schema changes don't break existing queries - **Path finding**: Shortest route, network analysis, dependency chains - **Pattern matching**: Fraud detection, recommendation engines, access control **Do NOT use graph databases when**: - Fixed schema with shallow joins (2-3 tables) → Use PostgreSQL - Primarily aggregations/analytics → Use columnar databases - Key-value lookups only → Use Redis/DynamoDB ## Quick Decision Framework ``` DATA CHARACTERISTICS? ├── Fixed schema, shallow joins (≤3 hops) │ └─ PostgreSQL (relational) │ ├── Already on PostgreSQL + simple graphs │ └─ Apache AGE (PostgreSQL extension) │ ├── Deep traversals (4+ hops) + general purpose │ └─ Neo4j (battle-tested, largest ecosystem) │ ├── Multi-model (documents + graph) │ └─ ArangoDB │ ├── AWS-native, serverless │ └─ Amazon Neptune │ └── Real-time streaming, in-memory └─ Memgraph ``` ## Core Concepts ### Property Graph Model Graph databases store data as: - **Nod