*Graph
Databases*, published by O’Reilly
Media, discusses the problems that are well
aligned with graph databases, with examples drawn from
practical, real-world use cases. This book also looks
at the ecosystem of complementary technologies,
highlighting what differentiates graph databases from
other database technologies, both relational and
NOSQL.

*Graph Databases* is written by Ian Robinson,
Jim Webber, and Emil Eifrém, graph experts
and enthusiasts at Neo Technology, creators of
Neo4j,
the world’s leading graph database.

#### Table of Contents

- 1. Introduction
- What is a Graph?

A High-Level View of the Graph Space

The Power of Graph Databases - 2. Options for Storing Connected Data
- Relational Databases Lack Relationships

NOSQL Databases Also Lack Relationships

Graph Databases Embrace Relationships - 3. Data Modeling with Graphs
- Models and Graphs

The Property Graph Model

Querying Graph: Introduction to Cypher

Comparison of Relational and Graph Modeling

Cross-Domain Models

Common Modeling Pitfalls

Avoiding Anti-Patterns - 4. Building a Graph Database Application
- Data Modeling

Application Architecture

Testing

Capacity Planning - 5. Graphs in the Real World
- Why Organizations Choose Graph Databases

Common Use Cases

Real-World Examples - 6. Graph Database Internals
- Native Graph Processing

Native Graph Storage

Programmatic APIs

Nonfunctional Characteristics - 7. Predictive Analysis with Graph Theory
- Depth- and Breadth- First Search

Path-Finding with Dijkstra’s Algorithm

The A* Algorithm

Graph Theory and Predictive Modeling

Local Bridges

This official released version of *Graph
Databases*, published by O’Reilly Media, is
compliments of Neo Technology, creators of
Neo4j.