Introduction data structure for GraphDB by Shunya Kimura.
Detailed examination of the data structures that manage nodes and relationships between nodes. Highly recommended.
Introduction data structure for GraphDB by Shunya Kimura.
Detailed examination of the data structures that manage nodes and relationships between nodes. Highly recommended.
GraphDB in PHP by Alessandro Nadalin and David Funaro.
Well, at 163 slides you know there is going to be some introductory graph material but it went by quickly enough. Would have liked to see the presentation that went with the slides but even without it, the slides are fairly interesting.
Good to see PHP libraries because PHP is so widely used as a scripting language. (No offense to others, just an observation. Use whatever is the most comfortable for you.)
Using A Graph Database To Power The “Web of Things”
From the post:
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.
Taped at QCon on 11 October 2011. Short of attending, it doesn’t get much fresher than that!
The Definition of GraphDB by Takahiro Inoue.
Yes, GraphDB is also a product name from Sones but in this context it means graph database in the generic sense.
Good thing we don’t have naming issues in the topic map/semantic integration area, would make it hard to find things. 😉
These are some of the best graphics I have ever seen for introducing graphs and their capabilities as data structures.
Definitely worth spending some time with them and forwarding to others.
Introduction to Graph Databases
From the description:
Neo Technology CEO Emil Eifrem provides a fast paced introduction to NOSQL, graph databases, and Neo4j, the world’s leading graph database.
I managed to catch this Webinar and it is a good introduction to graph databases.
From the press release on GraphDB 2.0:
– High-performance graph database based on a property hypergraph – Optimized for multiprocessor/multicore systems – Platform-independent (Linux, Windows, OSX) – Modular architecture – OpenSource (AGPLv3) and proprietary enterprise license – Intuitive, easy-to-learn query language: GQL (Graph Query Language) – Powerful API and traverse API – Integrated REST interfaces and administration tools – Optional persistence plug-ins – Client libraries in many popular programming languages (Java, C#, Javascript, PHP, …) – Integrated Javascript UI
Another OpenSource high performance graph database.
Graph databases seem to be on the rise in popularity.
Can model the relational model and more with graph databases.
But is that like markup trees being subsets of graphs?
That we find it easier to use subsets of the capabilities of graphs?
General overview of Neo4J, FlockDB, AllegroGraph, GraphDB, InfiniteGraph.
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