Graph databases store nodes (entities) and edges (relationships). Traversing relationships is time per hop with space, compared to joins.
Examples: Neo4j, Amazon Neptune, JanusGraph. Query languages like Cypher make relationship queries natural.
Use cases: Social networks, recommendation engines, fraud detection, knowledge graphs. When your questions are "who knows who" or "what's connected to what," graph databases shine. LinkedIn uses graphs for connection recommendations.