The property-graph model explained from first principles: nodes, relationships, and properties; Cypher queries for real traversal problems; why index-free adjacency beats recursive SQL CTEs for deep graph walks; fraud detection, recommendations, and knowledge graphs as concrete production use cases; Neo4j clustering and causal consistency; and an honest accounting of when adding a graph database is the wrong call.
Graph-Databases
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Graph Databases with Neo4j