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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

Key attributes of Cypher


In making Cypher, Neo Technology and Andres Taylor (@andres_taylor) set out to create a new query language, specifically to deal with graph data structures like the ones that we store in Neo4j. There were a couple of reasons for this; more specifically, there are four attributes that are not available together in any other query language out there.

Let's quickly examine these attributes, as they are quite important in understanding the way Cypher works in Neo4j:

  • Declarative: Cypher is a declarative query language, which is very different from the imperative alternatives out there. You declare the pattern that you are looking for. You effectively tell Cypher what you want, not how to get it. This is crucial, as imperative approaches always suppose that you--as you interact with the database--have the following qualities:
    • Are a programmer who knows how to tell the database what to do--probably with some procedural logic that will need to be formalized in a program.
    • Are...
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