Foreword

The database world is experiencing an enormous upheaval, with the hegemony of relational databases being challenged by a plethora of new technologies under the NoSQL banner. Among these approaches, graphs are gaining substantial credibility as a means of analyzing data across a broad range of domains.

Most NoSQL databases address the perceived performance limitations of relational databases, which flounder when confronted with the exponential growth in data volumes that we’ve witnessed over the last few years. But data growth is only one of the challenges we face. Not only is data growing, it’s also becoming more interconnected and more variably structured. In short, it’s becoming far more networked.

In addressing performance and scalability, NoSQL has generally given up on the capabilities of the relational model with regard to interconnected data. Graph databases, in contrast, revitalize the world of connected data, outperforming relational databases by several orders of magnitude. Many of the most interesting questions we want to ask of our data require us to understand not only that things are connected, but also the differences between those connections. Graph databases offer the most powerful and best-performing means for generating this kind of insight.