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  • Book Overview & Buying Neo4j High Performance
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Neo4j High Performance

Neo4j High Performance

By : Sonal Raj
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Neo4j High Performance

Neo4j High Performance

1 (1)
By: Sonal Raj
Buy this Book

Overview of this book

If you are a professional or enthusiast who has a basic understanding of graphs or has basic knowledge of Neo4j operations, this is the book for you. Although it is targeted at an advanced user base, this book can be used by beginners as it touches upon the basics. So, if you are passionate about taming complex data with the help of graphs and building high performance applications, you will be able to get valuable insights from this book.
Table of Contents (10 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Getting Started with Neo4j
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1. Getting Started with Neo4j
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Graphs and their utilities
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Types of NoSQL databases
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The Neo4j graph database
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The Neo4j setup and configurations
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Configure Neo4j for Amazon clusters
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Cloud deployment with Azure
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Summary
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2. Querying and Indexing in Neo4j
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2. Querying and Indexing in Neo4j
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The Neo4j interface
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Introduction to Cypher
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Cypher graph operations
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Advanced Cypher tricks
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Gremlin – an overview
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Indexing in Neo4j
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Migration techniques for SQL users
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Useful code snippets
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Summary
3
3. Efficient Data Modeling with Graphs
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3. Efficient Data Modeling with Graphs
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Data models
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Property graphs
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Design constraints in Neo4j
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Graph modeling techniques
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Schema design patterns
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Modeling across multiple domains
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Summary
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4. Neo4j for High-volume Applications
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4. Neo4j for High-volume Applications
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Graph processing
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Big data and graphs
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Processing with Hadoop or Neo4j
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Managing transactions
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The graphalgo package
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Introduction to Spring Data Neo4j
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Summary
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5. Testing and Scaling Neo4j Applications
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5. Testing and Scaling Neo4j Applications
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Testing Neo4j applications
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Unit testing
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Performance testing
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Benchmarking performance with Gatling
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Scaling Neo4j applications
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Summary
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6. Neo4j Internals
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6. Neo4j Internals
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Introduction to Neo4j internals
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Working of your code
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Storage for properties
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Caching internals
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Cache types
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Transactions
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High availability
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Summary
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7. Administering Neo4j
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7. Administering Neo4j
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Interfacing with the tools and frameworks
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Admin tricks
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Memory mapped I/O configuration
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Neo4j server logging
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Neo4j server security
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Summary
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8. Use Case – Similarity-based Recommendation System
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8. Use Case – Similarity-based Recommendation System
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The why and how of recommendations
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Building a recommendation system
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Recommendations on map data
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Visualization of graphs
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Summary
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Index
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Index

Data models

A data model tells us how the logical structure of a database is modeled. Data models are fundamental entities to introduce abstraction in DBMS. They define how data is connected to each other and how it will be processed and stored inside the system. There are two basic types of data models in which related data can be modeled: aggregated and connected.

The aggregated data model

Aggregated data is about how you might use aggregation in your model to simulate relationships when you can't explicitly define them. So, you might store different objects internally in separate sections of the data store and derive the relationships on the fly with the help of foreign keys, or any related fields between the object. Hence, you are aggregating data from different sources, for example, as depicted in the following diagram, a company might contain a collection of the people who work there, and a person might in turn be associated with several products within the company, from which you might...

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