{
"id": "stack-part:graph-database",
"_kind": "StackPart",
"_file": "domain/stack-parts/graph-database.yaml",
"_cluster": "domain",
"attributes": {
"displayName": "Graph Database",
"category": "data-store",
"description": "Database purpose-built for storing and traversing graph structures —\nnodes (entities) and edges (relationships) with properties on both.\nGraph databases excel at multi-hop relationship queries that would\nrequire expensive recursive joins in a relational database.\n\nCommon use cases: fraud detection, recommendation engines, knowledge\ngraphs, identity and access management, and social networks. Neo4j\nuses the Cypher query language; Amazon Neptune supports Gremlin and\nSPARQL; Dgraph uses GraphQL+DQL. Property graphs (Neo4j, Neptune) and\nRDF triplestores (Stardog, Amazon Neptune/SPARQL) are the two dominant\nparadigms. Vector + graph hybrids are emerging for AI knowledge graph\napplications.\n"
},
"outgoingEdges": [
{
"from": "stack-part:graph-database",
"to": "tool:neo4j",
"kind": "implemented_by",
"attributes": {}
}
],
"incomingEdges": [
{
"from": "tool:neo4j",
"to": "stack-part:graph-database",
"kind": "implements_stack_part",
"attributes": {}
}
]
}