Graph databases and social graph Graph databases are the most scalable, high-performance way to query and store highly interconnected data. They help improve intelligence, predictive analytics, social network analysis, and decision and process management – which all involve highly connected data with lots of relationships. A relevant use case for graph databases is the social graph.

From websites adding social capabilities to telcos providing personalized customer services, to innovative bioinformatics research, organizations are integrating graphs into their websites. Many high-profile companies are specifically adopting graph databases to solve social graph complexities and meet the high query performance levels required at the Internet scale. As websites scale from zero to millions of users, traditional relational databases degrade to paralyzing performance levels.

This talk will talk about what are graphs, how graphs came into existence, what are graph databases, why graphs matter, and how graphs help in solving critical business problems. Social graph database technology will become a key trend in the data science arena throughout 2012 and beyond. If an organization’s data contains a lot of many-to-many relationships, if recursive self-joins are too costly or limiting to the application and scaling needs, and/or the primary objective is quickly finding connections, patterns and relationships between the objects within lots of data, graph databases are the best solution.

Technical level: Beginner friendly

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