7 Advanced data modeling techniques

 

This chapter covers

  • Applying the data modeling process to more complex use cases
  • Improving performance by using generic labels
  • Denormalizing data for more efficient graph traversals
  • Moving properties to edges to simplify traversals

So far, we’ve walked through the entire process of building a simple graph application. We went from data modeling to traversal construction to coding a Java application for the recursive and pathfinding traversals that we used in our social network. Although the model for our social network was simplistic, it allowed us to demonstrate the patterns and processes required to build graph-backed applications, while showing some of the powerful tools, such as recursive and pathfinding traversals, that graphs bring to the table.

7.1 Reviewing our current data models

7.2 Extending our logical data model

7.3 Translating entities to vertices

7.3.1 Using generic labels

7.3.2 Denormalizing graph data

7.3.3 Translating relationships to edges

7.3.4 Finding and assigning properties

7.3.5 Moving properties to edges

7.3.6 Checking our model

7.4 Extending our data model for personalization

7.5 Comparing the results

Summary