Emil Eifrem
Founder of Neo4j
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.
- Neo4j
- Emil's Blog
- Follow @emileifrem on Twitter
Emil Eifrem is Giving the Following Talks
Neo4j -- my nosql database is not built in Erlang but I still <3 you!!
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 is difficult to deal with recursive data structures in traditional relational databases and many NoSQL stores alike. 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" (http://neo4j.org), which frequently outperforms relational backends with >1000x for graph-shaped data.
This turns out to be a problem because it is difficult to deal with recursive data structures in traditional relational databases and many NoSQL stores alike. 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" (http://neo4j.org), which frequently outperforms relational backends with >1000x for graph-shaped data.
