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Learning Neo4j

You're reading from   Learning Neo4j Run blazingly fast queries on complex graph datasets with the power of the Neo4j graph database

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Product type Paperback
Published in Aug 2014
Publisher
ISBN-13 9781849517164
Length 222 pages
Edition 1st Edition
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Author (1):
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Rik Van Bruggen Rik Van Bruggen
Author Profile Icon Rik Van Bruggen
Rik Van Bruggen
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Table of Contents (13) Chapters Close

Preface 1. Graphs and Graph Theory – an Introduction FREE CHAPTER 2. Graph Databases – Overview 3. Getting Started with Neo4j 4. Modeling Data for Neo4j 5. Importing Data into Neo4j 6. Use Case Example – Recommendations 7. Use Case Example – Impact Analysis and Simulation 8. Visualizations for Neo4j 9. Other Tools Related to Neo4j A. Where to Find More Information Related to Neo4j B. Getting Started with Cypher Index

The four fundamental data constructs


As you may already know by now, 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 the individual books, readers, and authors that are present in the library data model.

  • Relationships: These are used to connect nodes to one another explicitly and therefore provide a means of structuring your entities. They are the equivalent of an explicitly stored, and...

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