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Neo4j Graph Data Modelling

You're reading from   Neo4j Graph Data Modelling Design efficient and flexible databases by optimizing the power of Neo4j

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Product type Paperback
Published in Jul 2015
Publisher
ISBN-13 9781784393441
Length 138 pages
Edition 1st Edition
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Concepts
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Author (1):
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Mahesh K Lal Mahesh K Lal
Author Profile Icon Mahesh K Lal
Mahesh K Lal
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Table of Contents (11) Chapters Close

Preface 1. Graphs Are Everywhere 2. Modeling Flights and Cities FREE CHAPTER 3. Formulating an Itinerary 4. Modeling Bookings and Users 5. Refactoring the Data Model 6. Modeling Communication Chains 7. Modeling Access Control 8. Recommendations and Analysis of Historical Data 9. Wrapping Up 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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