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  • Neo4j Graph Data Modelling
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Neo4j Graph Data Modelling

Neo4j Graph Data Modelling

By : Mahesh K Lal
3 (1)
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Neo4j Graph Data Modelling

Neo4j Graph Data Modelling

3 (1)
By: Mahesh K Lal

Overview of this book

If you are a developer who wants to understand the fundamentals of modeling data in Neo4j and how it can be used to model full-fledged applications, then this book is for you. Some understanding of domain modeling may be advantageous but is not essential.
Table of Contents (11 chapters)
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Preface
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Free Chapter
1
1. Graphs Are Everywhere
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1. Graphs Are Everywhere
Graphs in mathematics
The property graph model
Storage – native graph storage versus non-native graph storage
Reasons to use graph databases
What to use a graph database for
Choosing Neo4j for exploring graph databases
The structure of the book
Summary
2
2. Modeling Flights and Cities
2. Modeling Flights and Cities
Graphs are more than social
Designing a system to get a travel itinerary
Introduction to modeling nodes and relationships
Using Cypher to operate on Neo4j
Creating cities in Neo4j
Indices
Adding flights to Neo4j
Traversing relationships
Summary
3
3. Formulating an Itinerary
3. Formulating an Itinerary
Creating an itinerary from flights and cities
Business logic should lie in code
Summary
4
4. Modeling Bookings and Users
4. Modeling Bookings and Users
Building a data model for booking flights
A simple model of the bookings ecosystem
Modeling bookings in an RDBMS
Creating bookings and users in Neo4j
Queries to find journeys and bookings
Queries to find the booking history of a user
Summary
5
5. Refactoring the Data Model
5. Refactoring the Data Model
Capturing information about hotels at airports
Modeling airports and hotels
Extracting airport information from flights
Reasons for not migrating using a single query
Adding hotels to airports
Fetching hotels
Summary
6
6. Modeling Communication Chains
6. Modeling Communication Chains
Capturing traveler reviews for hotels
A model for reviews and comments
Adding reviews to Neo4j
Adding comments to Neo4j
Summary
7
7. Modeling Access Control
7. Modeling Access Control
Controlling access for content change
Modeling hierarchies
Modeling access control groups and employees
Querying the data model to find what is accessible to an employee
Summary
8
8. Recommendations and Analysis of Historical Data
8. Recommendations and Analysis of Historical Data
Recommending cities to travelers
Recommending hotels to travelers
Analysis of the historical data
Summary
9
9. Wrapping Up
9. Wrapping Up
There is no correct model
Further reading and exploration
What to watch out for while using Neo4j
10
Index
Index

Choosing Neo4j for exploring graph databases

Neo4j is a fast, native graph database that satisfies Atomicity, Consistency, Isolation, Durability (ACID) properties. Through usage of transactions, developers can ensure that the failure of a transaction leaves the database's state unchanged ensuring atomicity. Any change to the database doesn't destroy data, ensuring consistency. Data modified by a transaction is isolated from other transactions till it is committed. Since Neo4j is a persistent graph database, the results of a committed transaction can always be retrieved, thus making it durable.

It started off supporting the TinkerPop stack. More information about the TinkerPop stack can be found at http://www.tinkerpop.com.

Neo4j provides numerous modeling and technical affordances, which are valuable when building real-world systems such as:

  • Neo4j is the most mature graph database and has been in production round the clock since 2003. Neo4j is open source with an enormous community. The Neo4j development team is highly engaged with that community so that the features and bugs are rapidly addressed. Neo4j provides native graph storage that enables its engine to perform native graph processing. From the query language to disks, everything is mechanically sympathetic to the transactional storage and rapid retrieval of graph data.
  • Cypher is a very expressive query language used to retrieve data from Neo4j. While it is superficially similar to SQL in some respect, Cypher is the only declarative query language that is built ground-up for humane yet performant graph queries and writes. The Neo4j Java API can be used on JVM-based languages as a more imperative and performant method of querying. This gives the best of both worlds by supporting imperative and declarative querying. (Neo4j plans to move away from supporting Gremlin in the long run, and currently Gremlin is supported through a plugin). Neo4j is open source and allows plugins to enhance or add functionalities, and there is a vibrant ecosystem of tooling around the core database.
  • Any Cypher statement that updates the graph is run within a transaction. If a transaction exists, the newly fired Cypher query will be run in it. If no transaction exists, then the statement will itself be transactional.
  • The community being fostered is incredible. This is also partly made possible by the project being open source. Neo4j is currently being used in production by companies such as UBS, Cisco, Walmart, eBay, Telenor, HP, Pitney Bowes, Accenture, Lockheed Martin, Glassdoor, and many others.
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