Book Image

Learning Neo4j 3.x - Second Edition

By : Jerome Baton
Book Image

Learning Neo4j 3.x - Second Edition

By: Jerome Baton

Overview of this book

Neo4j is a graph database that allows traversing huge amounts of data with ease. This book aims at quickly getting you started with the popular graph database Neo4j. Starting with a brief introduction to graph theory, this book will show you the advantages of using graph databases along with data modeling techniques for graph databases. You'll gain practical hands-on experience with commonly used and lesser known features for updating graph store with Neo4j's Cypher query language. Furthermore, you'll also learn to create awesome procedures using APOC and extend Neo4j's functionality, enabling integration, algorithmic analysis, and other advanced spatial operation capabilities on data. Through the course of the book you will come across implementation examples on the latest updates in Neo4j, such as in-graph indexes, scaling, performance improvements, visualization, data refactoring techniques, security enhancements, and much more. By the end of the book, you'll have gained the skills to design and implement modern spatial applications, from graphing data to unraveling business capabilities with the help of real-world use cases.
Table of Contents (24 chapters)
Title Page
Credits
About the Authors
Acknowledgement
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Summary


In this chapter, we illustrated that graph databases such as Neo4j are extremely well placed at playing a role in many enterprise architectures where impact analysis and simulation is important. There are many different fields where this may be useful, but we chose two specific domains to illustrate this use case. First, we took a look at a business process management use case, where analyzing and understanding the potential impact of a change in a network would be of primary interest to the user. Then, we took a look at an impact simulation use case, where we wanted to set up a use case in which we could iteratively simulate different impact scenarios and see what the result of those changes on the network would be, using a product hierarchy as an example to do so.

We hope we have given you a good overview of the use case and its potential.