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Neo4j is a robust, high performance, scalable graph database. It is the only NOSQL database that solves the complex, connected data challenges that enterprises face today.
Neo4j Commercial Licensing Options
Learn which Neo4j commercial license is right for you.
Neo4j is a dual-licensed commercial open-source database. How can Neo4j be both commercial and open source? How can a business safely use open source software?
For a clear understanding of how Neo4j is both commercial and open-source, Andreas Kollegger takes a closer look at Neo Technology’s dual-license business model, and identifies key differentiators in order to make an educated decision for your particular use case.
This whitepaper is intended for enterprise professionals who want to better understand the full, robust benefits from Neo Technology, accompanied by technical support for their organization.
Mini Book: The Spring Data Neo4j Tutorial
The Spring Data Neo4j Tutorial minibook is now available on InfoQ. Download your copy today.
This tutorial walks through the creation of a complete web application called cineasts.net, built with Spring Data Neo4j. The tutorial takes the reader through the steps necessary to create the application. It provides the configuration and code examples that are needed to understand what's happening in Spring Data Neo4j.
WEBINARS
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Hardware Sizing with Neo4j
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Understand Neo4j Commercial Licenses |
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Neo4j in the Trenches: OpenCredo Talks Social |
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PRESENTATIONS
Highly Connected Data Models in NOSQL Stores
In this talk, Jim Webber discusses the key ideas of NOSQL databases, including motivating similarities and more importantly their different strengths and weaknesses. Jim focuses on the characteristics of graph stores for connected data and the kinds of problems for which they are best suited.
Recorded at YOW! Melbourne
Introduction to Spring Data Neo4j - Presentation
Michael Hunger discusses graph databases and the need for them in the larger context of NoSQL data stores.
Recorded at Springone2gx 2011, Michael introduces Spring Data, Neo4j, and Spring Data Neo4j.
Using A Graph Database To Power The "Web of Things"
Rick Bullotta and Emil Eifrem discuss how to use graph databases to model the real world, people, systems and things, talking advantage of the relationships between various data elements.
MEDIA
IBM Podcast: Emil Eifrem, The Man Behind Neo4j
Andrew Glover interviews the CEO of Neo Technology to discuss graphs relevance in today's highly connected world.
Neo4j: Social Skills for Ruby Developers
Prasanna Pendse discusses FitStudio, a social app powered by Sears, and how it was developed on Neo4j.
Heroku, Neo4j and Google Spreadsheet in 10min. Flat.
A screencast about deploying an application using the Neo4j add-on on Heroku to expose a readonly Cypher endpoint. Then integrating with a Google Spreadsheet for querying and rendering of the results. For step by step instructions, code and sample data go here.
ARTICLES
Philip Howard writes 5 articles that discuss graph databases, its technology and why they are the next big thing.
Forrester Big Data Predictions for 2012: Graph Databases
James Kobielus blogs about his predictions for big data in 2012, and highlights that "the market for graph databases will boom in 2012 as companies everywhere adopt them for social media analytics, marketing campaign optimization, and customer experience fine-tuning."
Edd Dumbill from O'Reilly Radar introduces the big data landscape, and explains how graph databases like Neo4j make operations on social network relations more simple and efficient.
Graph Databases, NOSQL and Neo4j
Peter Neubauer introduces Graph databases and how they compare to RDBMS' and where they stand in the NOSQL-movement, followed by examples of using a graph database in Java with Neo4j.
The NoSQL movement is here to stay. The need for reliable storage that can be easily queried and easily scalable without the pain of SQL schema migration is real. Developers want more agile systems. This article uses MongoDB to introduce NoSQL concepts. This article covers the basics of MongoDB architecture, caveats and programming in MongoDB for Java, PHP, and Python developers.
Recently Couchbase published a comparison of Couchbase and CouchDB to denote the differences and simlarities between the two. This document addresses a common question: "What is the difference between CouchDB and Couchbase?", and what happened to Membase? InfoQ caught up with James Phillips, a Couchbase founder, to discuss the comparison and the merger of the two products Membase and CouchDB.
Developed since 2010 by Rich Hickey and the Relevance team, Datomic offers some new approaches to database architecture. Leveraging current trends in cloud and storage it has strong transactions, rich query API and read scaling.
NServiceBus 3.0 was recently released and InfoQ talked to Udi Dahan, the creator of NServiceBus, about the new features of the latest release. One of which is the RavenDb integration, a fairly new document data store written in .NET and created by Oren Eini (Ayende). InfoQ also took the opportunity to ask Ayende some questions and what the integration means for his own Rhino Service Bus.
Brian C. Dilley covers pitfalls, & strengths of using MongoDB ("a very approachable NoSQL solution"), and introduces MJORM. The MJORM project is an annotation free MongoDB Java ORM library. This article builds on Brian's real world in the trenches experience with MongoDB and includes "gotchas" like "Don't treat MongoDB like an RDBMS...", how to "design your indexes carefully", and more.
NoSQL databases offer alternative data storage options for storing unstructured data compared to traditional relational databases. Though the NoSQL databases have been getting a lot of attention lately, the security aspects of storing and accessing NoSQL data haven't been given much emphasis. This article focuses on the security considerations and best practices in accessing the NoSQL databases.
With the recent NoSQL movement there are several alternative data storage solutions available compared to the traditional relational databases. In this article, author Srinath Perera discusses the various data storage options and what to consider when choosing each of these solutions.
Sid Anand presents the architecture set in place at LinkedIn and the data infrastructure running Java and Scala apps on top of Oracle, Voldemort, DataBus and Kafka.
Susan Potter discusses Dynamo, Riak, distribution, consistency and fault tolerance, along with techniques and an example for building an application with riak_core.
In this interview at QCon London, LinkedIn’s Sid Anand discusses the problems they face when serving high-traffic, high-volume data. Sid explains how they’re moving some use cases from Oracle to gain headroom, and lifts the hood on their open source search and data replication projects, including Kafka, Voldemort, Espresso and Databus.
Rich Hickey explains the ideas behind the Datomic database: why Datalog is used as the query language, the functional programming concepts at its core, the role of time in the DB and much more.
With Spring Data, the ever popular Spring Framework has cultivated a new patch of ground, bringing Big Data and NOSQL technology like Neo4j to enterprise developers. This guide introduces you to Spring Data Neo4j, using the fast, powerful and scalable graph database Neo4j to enjoy the benefits of having good relationships in your data.
