Learning Neo4j 3.x, 2nd Edition

Learning Neo4j 3.x, 2nd Edition

English | 2017 | ISBN: 978-1786466143 | 316 Pages | PDF, EPUB, MOBI | 209 MB

Effective data modeling, performance tuning and data visualization techniques in Neo4j
Run blazingly fast queries on complex graph datasets with the power of the Neo4j graph database
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.
What You Will Learn

  • Understand the science of graph theory, databases and its advantages over traditional databases.
  • Install Neo4j, model data and learn the most common practices of traversing data
  • Learn the Cypher query language and tailor-made procedures to analyze and derive meaningful representations of data
  • Improve graph techniques with the help of precise procedures in the APOC library
  • Use Neo4j advanced extensions and plugins for performance optimization.
  • Understand how Neo4j’s new security features and clustering architecture are used for large scale deployments.
Homepage