Databases Reference
In-Depth Information
CHAPTER 5
Graphs in the Real World
In this chapter we look at some of the common real-world use cases for graph databases
and identify the reasons why organizations choose to use a graph database rather than
a relational or other NOSQL store. The bulk of the chapter comprises three in-depth
use cases, with details of the relevant data models and queries. Each of these examples
has been drawn from a real-world production system; the names, however, have been
changed, and the technical details simplified where necessary to hide any accidental
complexity, and thereby highlight key design points.
Why Organizations Choose Graph Databases
Throughout this topic, we've sung the praises of the graph data model, its power and
flexibility, and its innate expressiveness. When it comes to applying a graph database to
a real-world problem, with real-world technical and business constraints, organizations
choose graph databases for the following reasons:
“Minutes to milliseconds” performance
Query performance and responsiveness are top of many organizations' concerns
with regard to their data platforms. Online transactional systems, large web appli‐
cations in particular, must respond to end users in milliseconds if they are to be
successful. In the relational world, as an application's dataset size grows, join pains
begin to manifest themselves, and performance deteriorates. Using index-free ad‐
jacency, a graph database turns complex joins into fast graph traversals, thereby
maintaining millisecond performance irrespective of the overall size of the dataset.
Drastically accelerated development cycles
The graph data model reduces the impedance mismatch that has plagued software
development for decades, thereby reducing the development overhead of translat‐
ing back and forth between an object model and a tabular relational model. More
importantly, the graph model reduces the impedance mismatch between the
