Database Reference
In-Depth Information
Q2. Normalization is expensive in a graph database model.
1.
True
2.
False
Q3. If you have a few entities in your dataset that have lots of relationships to other
entities, then you can't use a graph database because of the dense node problem.
1.
True—you will have to use a relational system
2.
True—but there is no alternative, so you will have to live with it
3.
False—you can still use a graph database but it will be painfully slow for
all queries
4.
False—you can very effectively use a graph database, but you should take
precautions, for example, applying a fan-out pattern to your data
Summary
In this chapter, we discussed a number of topics that will help you get started when
modeling your domain for a graph database management system. We talked about
the fundamental building blocks of the model, compared and contrasted this with the
way we do things in a relational database management system, and then discussed
some often recurring patterns, both good and bad, for doing the modeling work.
Withthemodelbehindus,wecannowstarttacklingspeciicbusinessproblemsusing
Neo4j. In the next chapter, we will start discussing the different data import strategies
thatwillilltheNeo4jdatabasewithdomain-speciicdatasets.
