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Using Neo4j to Index the World

Neo4jLarge organizations are beginning to use impressive indexing techniques to find insight as indexing becomes a crucial part of truly understanding big data.

For example, Facebook’s effort to tag and index over a trillion posts, detailed by Josh Constine of TechCrunch, is part of their overall goal to better target advertisements to its user base.

As Constine puts it, “Facebook’s product depends on guessing what we want based on who we were.”

Instead of only having access to people’s likes and locations and interests, Facebook will potentially now have the ability to mine things like sentiment and syntax to further personalize the ads on your timeline.

This kind of intensive tagging and indexing mechanism can also be made possible by the Neo4j graph database. Indeed, FlockData uses Neo4j to do just that.

Neo4j allows for smarter and simpler caching that doesn’t muck up the back-end code. For FlockData, that means important information is readily available whenever you need it.