Graph DBs are great for intersection queries (AND queries). In fact, DGraph is designed to do those really fast; and supporting that via GraphQL is in our roadmap.
In general Graph DBs are great when you have many "kinds" of things, which would require many many tables in traditional databases, and lots of interlinking. Those scenarios are ideal for Graphs, because many different kinds of things can be interrelated to each other easily, and be queried seamlessly. In other words, the schema for graphs is very fluid.
Maybe this exists already and I just haven't found it but I would love to find a tool that visually/graphically helps me visualize and test build data structures for a graph database. For example modeling the relationship from a host to VM to OS to app to network etc.
Check out the Assimilation Project [1]. It facilitates automatic infrastructure discovery and uses the Neo4j graph database for visualization / querying. More info about the project here [2].
Our users (graphistry.com) do this with our visualizer. You don't really need a heavy-duty graph database for that part, stuff like SQL or even lighter weight things are more normal.
It gets fun for us when we help visualize a full enterprise (hundreds of thousands of users, devices, apps..), and even more so when event data enters the picture. We do the former with our GPU tech, and push the latter to generic big data systems like Spark or Splunk that should already be in place before this becomes worthwhile.
https://github.com/dgraph-io/dgraph/issues/1
In general Graph DBs are great when you have many "kinds" of things, which would require many many tables in traditional databases, and lots of interlinking. Those scenarios are ideal for Graphs, because many different kinds of things can be interrelated to each other easily, and be queried seamlessly. In other words, the schema for graphs is very fluid.