Because of Neo4j's focus on node/edge traversal, it is a good fit for use cases requiring analysis and examination of relationships. The property graph model helps to define those relationships in meaningful ways, enabling the user to make informed decisions. Bearing that in mind, there are several use cases for Neo4j (and other graph databases) that seem to fit naturally.
Social networks seem to be a natural fit for graph databases. Individuals have friends, attend events, check in to geographical locations, create posts, and send messages. All of these different aspects can be tracked and managed with a graph database such as Neo4j.
Who can see a certain person's posts? Friends? Friends of friends? Who will be attending a certain event? How is a person connected to others attending the same event? In small numbers, these problems could be solved with a number of data stores. But what about an event with several thousand people attending, where each...