Graph Database

A graph database stores data as nodes (entities) and edges (relationships between entities), treating the connections as first-class data equal in importance to the entities themselves. This model is ideal for domains where relationships are as meaningful as the data points.

Graph databases excel at traversal queries that are expensive in relational databases: 'find all properties within two hops of this location', 'identify all funds that have invested in the same companies as a specific manager', or 'which products are frequently purchased together'. Common graph databases include Neo4j, Amazon Neptune, and ArangoDB.

For most API and dataset use cases, SQL or NoSQL databases are more appropriate than graph databases. Graph databases become the right choice when your primary analytical queries involve traversing complex many-to-many relationship networks across large numbers of entities.