This technical book, "Graph Databases" by Jim Webber, published in 2013, provides an in-depth exploration of graph database technology. Authored by Jim Webber, with contributions from Ian Robinson and Emil Eifrem, this work delves into the design and implementation of graph databases, focusing on the Property Graph Model and the Cypher query language. It is intended for professionals seeking to understand and leverage graph databases for various applications, covering essential topics such as data modeling best practices, test-driven development, real-world examples, architecture patterns, analytical techniques, and algorithms.
This manual serves as a comprehensive resource for understanding graph databases. It details the core concepts, practical applications, and advanced techniques necessary for effective database management and design. The content is structured to assist users in implementing and optimizing graph database solutions, offering insights into their architecture and analytical capabilities. This book is an invaluable guide for anyone involved in data modeling, database management, or data processing, aiming to enhance their expertise in this specialized field.
Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems.
Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution.
- Model data with the Cypher query language and property graph model
- Learn best practices and common pitfalls when modeling with graphs
- Plan and implement a graph database solution in test-driven fashion
- Explore real-world examples to learn how and why organizations use a graph database
- Understand common patterns and components of graph database architecture
- Use analytical techniques and algorithms to mine graph database information
Author: Robinson, Ian
Author: Webber, Jim
Author: Eifrem, Emil
Publisher: O'Reilly Media
Illustration: N
Language: ENG
Title: Graph Databases
Pages: 00224 (Unencrypted EPUB)
On Sale: 2013-07-18
SKU-13/ISBN: 9781449356262
Category: Computers : Data Modeling & Design
Category: Computers : Data Processing
Category: Computers : Database Management - Data Warehousing
Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems.
Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution.
- Model data with the Cypher query language and property graph model
- Learn best practices and common pitfalls when modeling with graphs
- Plan and implement a graph database solution in test-driven fashion
- Explore real-world examples to learn how and why organizations use a graph database
- Understand common patterns and components of graph database architecture
- Use analytical techniques and algorithms to mine graph database information
Author: Robinson, Ian
Author: Webber, Jim
Author: Eifrem, Emil
Publisher: O'Reilly Media
Illustration: N
Language: ENG
Title: Graph Databases
Pages: 00224 (Unencrypted EPUB)
On Sale: 2013-07-18
SKU-13/ISBN: 9781449356262
Category: Computers : Data Modeling & Design
Category: Computers : Data Processing
Category: Computers : Database Management - Data Warehousing
