ISWC Meetup with Neo4J: Difference between revisions
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Video: [http://blip.tv/file/2895759 Lotico Meetup with Neo4J at ISWC 2009] [http://blip.tv/rss/flash/2915529 Flash Video] | |||
Date: October 27, 2009 | |||
Video Edit: Ra'Shaun Stovall | |||
Speaker: Emil Eifrem Neo4j | |||
Host: Marco Neumann KONA | |||
Location: [http://iswc2009.semanticweb.org/ ISWC 2009] - 14750 Conference Center Drive, Chantilly, Virginia 20151 USA | |||
== Neo4j - The Benefits of Graph Databases == | == Neo4j - The Benefits of Graph Databases and Property Graphs== | ||
Emil Eifrém, CEO Neo4j | Graph Database Systems & Neo4j - Exploring the relationship between Property Graph Systems and Semantic Web Databases. | ||
[[Emil Eifrém]], CEO Neo4j | |||
Description | Description | ||
Meet Emil Eifrém CEO Neo Technology, founder of the Neo4j graph database project and CEO of Neo Technology. Programmer by passion the first 15 years on this planet and by passion & profession the remaining 15. First free software project at age 16. Now mainly | Meet [[Emil Eifrém]] CEO Neo Technology, founder of the Neo4j graph database project and CEO of Neo Technology. Programmer by passion the first 15 years on this planet and by passion & profession the remaining 15. First free software project at age 16. Now mainly focused on spreading the word about the powers of graphs and preaching the demise of tabular solutions everywhere. Presents regularly at conferences such as JAOO, Oredev, QCon, and OSCON. | ||
focused on spreading the word about the powers of graphs and preaching the demise of tabular solutions everywhere. Presents regularly at conferences such as JAOO, Oredev, QCon, and OSCON. | |||
Many applications today handle data that is deeply associative, i.e. structured as graphs (networks). The most obvious example of this is social networking sites, but even tagging systems, content management systems and wikis deal with inherently hierarchical or graph-shaped data. | |||
This turns out to be a problem because it’s difficult to deal with recursive data structures in both traditional relational databases and many NoSQL stores. For example, in an RDBMS each traversal along a link in a graph is a join, and joins are known to be very expensive. | |||
A graph database uses nodes, relationships between nodes and key-value properties instead of tables to represent information. This model is typically substantially faster for associative data sets and uses a schema-less, bottoms-up model that is ideal for capturing ad-hoc and rapidly changing data. | |||
This session will introduce an open source, high-performance, transactional and disk-based graph database called “Neo4j”, which frequently outperforms relational backends with >1000x for many increasingly important use cases. | |||
===External Links=== | |||
http://neo4j.org | |||
[[category:event]] | |||
Latest revision as of 11:56, 6 November 2020
Video: Lotico Meetup with Neo4J at ISWC 2009 Flash Video
Date: October 27, 2009
Video Edit: Ra'Shaun Stovall
Speaker: Emil Eifrem Neo4j
Host: Marco Neumann KONA
Location: ISWC 2009 - 14750 Conference Center Drive, Chantilly, Virginia 20151 USA
Neo4j - The Benefits of Graph Databases and Property Graphs
Graph Database Systems & Neo4j - Exploring the relationship between Property Graph Systems and Semantic Web Databases.
Emil Eifrém, CEO Neo4j
Description
Meet Emil Eifrém CEO Neo Technology, founder of the Neo4j graph database project and CEO of Neo Technology. Programmer by passion the first 15 years on this planet and by passion & profession the remaining 15. First free software project at age 16. Now mainly focused on spreading the word about the powers of graphs and preaching the demise of tabular solutions everywhere. Presents regularly at conferences such as JAOO, Oredev, QCon, and OSCON.
Many applications today handle data that is deeply associative, i.e. structured as graphs (networks). The most obvious example of this is social networking sites, but even tagging systems, content management systems and wikis deal with inherently hierarchical or graph-shaped data.
This turns out to be a problem because it’s difficult to deal with recursive data structures in both traditional relational databases and many NoSQL stores. For example, in an RDBMS each traversal along a link in a graph is a join, and joins are known to be very expensive.
A graph database uses nodes, relationships between nodes and key-value properties instead of tables to represent information. This model is typically substantially faster for associative data sets and uses a schema-less, bottoms-up model that is ideal for capturing ad-hoc and rapidly changing data.
This session will introduce an open source, high-performance, transactional and disk-based graph database called “Neo4j”, which frequently outperforms relational backends with >1000x for many increasingly important use cases.