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Graph Databases Make Apps Social

Neo Technology has suggested that social graph database technology will become a key trend in the data science arena throughout 2012 and beyond. On the back of vindicating comments made by Forrester analyst James Kobielus, the company contends that social graph complexities are needed to meet the high query performance levels now required inside Internet scale cloud applications.

Unsurprisingly a vendor of graph database technology itself (although Neo4j is open source at heart before its commercially supported equivalent), Neo Technology points to social graph capabilities, which take information across a range of networks to understand the relationships between individuals.

"As websites scale from zero to millions of users, traditional relational databases degrade to paralyzing levels of performance. Graph databases, based on decades of research, model and query connected data without performance degradation as the size of the graph grows," said the company, in a press statement.

According to a blog post by Forrester's James Kobielus, the market for graph databases will boom in 2012 as companies everywhere adopt them for social media analytics.

"We will see VCs put big money behind graph database and analytics startups. Many big data platform and tool vendors will acquire the startups to supplement their expanding Hadoop, NoSQL, and enterprise data warehousing (EDW) portfolios. Social graph analysis, although not a brand-new field, will become one of the most prestigious specialties in the data science arena, focusing on high-powered drilldown into polystructured behavioral data sets," Kobielus wrote.

Neo Technology claims that graph database implementation now will help make applications more "social" in their nature. The firm says that Neo4j enables developers to harness the social graph concept as an "enabling technology" to develop applications for tasks as diverse as finding a job to sharing ideas within a workspace.

"We've seen first hand that socially enabled applications are gravitating towards graph databases because other types of databases are not effective for managing relationships between millions of users with multiple connections. A graph database is the ideal solution for any application that relies on the relationships between records," said Emil Eifrem, CEO, Neo Technology.

NOTE: In an Iowa State University paper, Adrian Silvescu, Doina Caragea, and Anna Atramentov provide the following conceptualization of graph databases:

Current representation and storage systems are not very flexible in dealing with big changes and also they are not concerned with the ability of performing complex data manipulations&ellipse;On the other hand, data manipulation systems cannot easily work with structural or relational data, but just with flat data representations. We want to bridge the gap between the two, by introducing a new type of database structure, called Graph Databases (GDB), based on a natural graph representation. Our Graph Databases are able to represent as graphs any kind of information, naturally accommodate changes in data, and they also make easier for Machine Learning methods to use the stored information.

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