If you are writing lots of joins in SQL, that might be a good use case for a graph database like Neo4j. Neo4j treats relationships as first class citizens, so really anytime you care about relationships in your data you might have a good graph use case.
One way to think about relationships in graph databases is as materialized joins. Relationships are modeled and stored explicitly so there is no join at query time, only a constant time graph traversal. There are differences in flexibility of data model, ease of expressing traversals in the query language, etc but I think traversal vs JOIN is a good way to compare relational vs graph.
One way to think about relationships in graph databases is as materialized joins. Relationships are modeled and stored explicitly so there is no join at query time, only a constant time graph traversal. There are differences in flexibility of data model, ease of expressing traversals in the query language, etc but I think traversal vs JOIN is a good way to compare relational vs graph.