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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
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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

The four fundamental data constructs

As you may already know, the graph theory gives us many different graphs to work with. Graphs come in many different shapes and sizes, and therefore, Neo4j needed to choose a very specific type of data structure that is flexible enough to support the versatility required by real-world datasets. This is why the underlying data model of Neo4j, the labeled property graph, is one of the most generic and versatile of all graph models.

This graph data model gives us four different fundamental building blocks to structure and store our data. Let's go through them:


The labeled property graph model
  • Nodes: These are typically used to store entity information. In the preceding example, these are individual books, readers, and authors that are present in the library data model.
  • Relationships: These are used to connect nodes to one another explicitly...
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