Introduction
More digital data is being collected today than ever before, amounting to an evergrowing goldmine of insights just waiting to be uncovered. Traditionally, software applications use relational databases to store, access, and analyze data. But, these days, as that data goldmine grows in size and complexity, so do our expectations of the kinds of insights that data can provide for us. The fact is, when it comes to delivering the most powerful insights, relational databases are falling short. That’s where graph databases come in.
In contrast to the orderly, rows-and-columns nature of relational databases, the structure of graph databases allows them to capture the web-like connections within the data, revealing those more unique and powerful insights that modern users demand—and they do it better, faster, and with less effort. To shine a spotlight on the strengths and benefits of graphs and their applications, we’ve chosen chapters from three excellent Manning books that explore the subject from a few different angles.
The first chapter, from our own book, Graph Databases in Action, jumps right into graph data modelling, a crucial first step in creating a mental picture of how to solve the problem at hand. Following our tried-and-true four-step process, you’ll go hands-on to build a data model for a social networking use case, paying special attention to details that lend a sophistication to data models that only graph data modeling can achieve.
Next, in a chapter from Alessandro Negro’s book, Graph-Powered Machine Learning, you’ll examine the role of graphs in machine learning as you take a look at a system for large scale graph processing, see how graphs can be used to break down complex processing tasks, and more. Ultimately, you’ll understand how graphs and machine learning work hand-in-hand to transform raw data into actionable wisdom, delivering superior results to end users, data analysts, and business people alike.
GraphQL, a high-utility, type-based query language, provides interaction with graph databases that’s developer-friendly and easy to understand. In the final chapter of this mini ebook, from GraphQL in Action by Samer Buna, you’ll use GraphQL’s feature- rich, interactive, in-browser IDE to perform queries and mutations, test examples, and learn the basic elements of a GraphQL request.
We believe these chapters provide a great starting point for learning about graph databases. If your interest in this fascinating—and timely—subject is piqued and you’re up for continuing your graph databases journey, we hope you’ll check out the complete versions of all the books in this sampler.