Graph Data Models
Outline
Labeled Property Graph (LPG)
- The Labeled Property Graph is the most widely adopted graph data model for enterprise applications, transactional systems (OLTP), and modern data architectures
- Structure: Consists of Nodes (entities), Edges/Relationships (directed connections between nodes), Labels (categorizing nodes/edges), and Properties (key-value pairs attached to both nodes and edges)
- Characteristics: Highly intuitive for modeling real-world domains (e.g., social networks, fraud detection, recommendation engines). It allows rich metadata to live directly on the relationships
- Query Languages: Associated with languages like Cypher (and openCypher), GSQL (TigerGraph), Gremlin (via Apache TinkerPop), and the standardized GQL (Graph Query Language)
- Popular Platforms: Neo4j, TigerGraph, Amazon Neptune, Memgraph, and ArangoDB
Labeled Property Graph (LPG)
- Example
(alice:Person {name: 'Alice', age: 30}), (bob:Person {name: 'Bob', age: 25}), (movie:Movie {title: 'Inception', year: 2010}), (alice)-[:FRIENDS_WITH {since: 2020}]->(bob), (alice)-[:ACTED_IN {role: 'Ariadne'}]->(movie), (bob)-[:WATCHED {rating: 5}]->(movie);
Graph Data Models
Outline
References
- Reference