Even though modeling graphs seems to be a quite expressive method of handling the level of complexity associated with a problem domain, this expressivity is not a guarantee that the graph is fit for the purpose it is designed for. There are several issues of wrong modeling among graph data users, but eventually, you learn which model is suitable for the scenario at hand.

In this chapter, we looked at how vivid modeling is possible when you have data in graphs. We also looked at how Neo4j data can be modeled with Cypher as a tool to decipher interesting relationships directly, which would otherwise require several hours of computation.

In the next chapter, we will look at scenarios that handle high-volume data in Neo4j applications.