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Graph Databases

New Opportunities for Connected Data

Paperback Engels 2015 9781491930892
Verkooppositie 2737Hoogste positie: 2737
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Samenvatting

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.

This second edition includes new code samples and diagrams, using the latest Neo4j syntax, as well as information on new functionality. 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

Specificaties

ISBN13:9781491930892
Taal:Engels
Bindwijze:paperback
Aantal pagina's:238
Uitgever:O'Reilly
Druk:2
Verschijningsdatum:5-7-2015
Hoofdrubriek:IT-management / ICT
ISSN:

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Over Ian Robinson

Ian Robinson is a Principal Consultant with ThoughtWorks, where he specialises in helping clients create sustainable service-oriented development capabilities that align business and IT from inception through to operation. He has written guidance for Microsoft on implementing service-oriented systems with Microsoft technologies, and has published articles on business-oriented development methodologies and distributed systems design - most recently in The ThoughtWorks Anthology (Pragmatic Programmers, 2008). He presents at conferences worldwide on RESTful enterprise integration and distributed systems design and delivery.

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Over Jim Webber

Jim Webber is the SOA practice lead for ThoughtWorks where he works on dependable service-oriented systems. Jim was formerly a senior researcher with the UK E-Science programme where he developed strategies for aligning Grid computing with Web Services practices and architectural patterns for dependable Service-Oriented computing. Jim has extensive Web Services architecture and development experience as an architect with Arjuna Technologies and was the lead developer with Hewlett-Packard on the industry's first Web Services Transaction solution. Jim is an active speaker in the Web Services space and is co-author of the book "Developing Enterprise Web Services - An Architect's Guide." Jim holds a B.Sc. in Computing Science and Ph.D. in Parallel Computing both from the University of Newcastle upon Tyne.

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Inhoudsopgave

Foreword
Preface

1. Introduction
-What Is a Graph?
-A High-Level View of the Graph Space
-The Power of Graph Databases
-Summary

2. Options for Storing Connected Data
-Relational Databases Lack Relationships
-NOSQL Databases Also Lack Relationships
-Graph Databases Embrace Relationships
-Summary

3. Data Modeling with Graphs
-Models and Goals
-The Labeled Property Graph Model
-Querying Graphs: An Introduction to Cypher
-A Comparison of Relational and Graph Modeling
-Cross-Domain Models
-Common Modeling Pitfalls
-Identifying Nodes and Relationships
-Avoiding Anti-Patterns
-Summary

4. Building a Graph Database Application
-Data Modeling
-Application Architecture
-Testing
-Capacity Planning
-Importing and Bulk Loading Data
-Summary

5. Graphs in the Real World
-Why Organizations Choose Graph Databases
-Common Use Cases
-Real-World Examples
-Summary

6. Graph Database Internals
-Native Graph Processing
-Native Graph Storage
-Programmatic APIs
-Nonfunctional Characteristics
-Summary

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
-Summary

Appendix A: NOSQL Overview

Index

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