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

Key operative words in Cypher


Like every database query language, there are a few operative words that have an important meaning in the composition of every query. It's useful for you to know these, as you will be using them to compose your specific queries on your specific datasets.

Keyword

Function

Example

MATCH

This describes a pattern that the database should match. This is probably the most important piece of the query as it is a structural component that always starts your queries (it's one character shorter than SELECT).

MATCH (me:Person)-[:KNOWS]->(friend)

WHERE

This filters results that are found in the match for specific criteria.

WHERE me.name = "My Name" AND me.age > 18

RETURN

This returns results. You can either return paths, nodes, relationships, or their properties, or an aggregate of the mentioned parameters. This is another structural component, as all read queries and most write queries will return some data.

RETURN me.name, collect(friend), count(*) as friends

WITH

This passes...