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Learning Neo4j 3.x

You're reading from   Learning Neo4j 3.x Effective data modeling, performance tuning and data visualization techniques in Neo4j

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781786466143
Length 316 pages
Edition 2nd Edition
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Authors (2):
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Jerome Baton Jerome Baton
Author Profile Icon Jerome Baton
Jerome Baton
Rik Van Bruggen Rik Van Bruggen
Author Profile Icon Rik Van Bruggen
Rik Van Bruggen
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Toc

Table of Contents (17) Chapters Close

Preface 1. Graph Theory and Databases FREE CHAPTER 2. Getting Started with Neo4j 3. Modeling Data for Neo4j 4. Getting Started with Cypher 5. Awesome Procedures on Cypher - APOC 6. Extending Cypher 7. Query Performance Tuning 8. Importing Data into Neo4j 9. Going Spatial 10. Security 11. Visualizations for Neo4j 12. Data Refactoring with Neo4j 13. Clustering 14. Use Case Example - Recommendations 15. Use Case Example - Impact Analysis and Simulation 16. Tips and Tricks

Key concepts and characteristics of Neo4j


Before we dive into the details of Neo4j, let's take a look at some of the key characteristics of Neo4j as a graph database management system, specifically. Hopefully, this will immediately point out and help you get to grips with some of the key strengths as well.

Built for graphs from the ground up

Like many open source projects and open source NoSQL database management systems, Neo4j came into existence for very specific reasons. Scratching the itch, as this is sometimes called. Grassroots developers who want to solve a problem and are struggling to do so with traditional technology stacks decide to take a radical, new-found approach. That's what the Neo4j founders did early in the 21st century--they built something to solve a problem for a particular media company in order to better manage media assets.

In the early days, Neo4j was not a full-on graph database management system; it was more like a graph library that people could use in their code...

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