We live in a connected world. To thrive and progress, we need to understand and influence the web of connections that surrounds us.
How do today’s technologies deal with the challenge of connected data? In this chapter we look at how relational databases and aggregate NOSQL stores manage graphs and connected data, and compare their performance to that of a graph database. For readers interested in exploring the topic of NOSQL, Appendix A describes the four major types of NOSQL databases.
For several decades, developers have tried to accommodate connected, semi-structured datasets inside relational databases. But whereas relational databases were initially designed to codify paper forms and tabular structures—something they do exceedingly well—they struggle when attempting to model the ad hoc, exceptional relationships that crop up in the real world. Ironically, relational databases deal poorly with relationships.
Relationships do exist in the vernacular of relational databases, but only as a means of joining tables. In our discussion of connected data in the previous chapter, we mentioned we often need to disambiguate the semantics of the relationships that connect entities, as well as qualify their weight or strength. Relational relations do nothing of the sort. Worse still, as outlier data multiplies, and the overall structure of the dataset becomes more complex and less uniform, the relational model ...