Graph databases store data as things and the connections between them.

They are useful when the connections are the main thing you need to query. Common examples include social networks, permissions, fraud rings, service dependencies, knowledge graphs, computer networks, and supply chains.

The practical question is not "does my data have relationships?" Most data does. The better question is: "Do my important queries follow relationships, walk paths, or look for patterns in connected data?"

If the answer is yes, a graph database may fit. If the system mostly fetches records by ID, filters rows, or calculates totals, a relational, document, key-value, or analytics database may be simpler.

This chapter covers the property graph model, how graph queries work, and when a graph database is the right fit.