Emil Eifrem of Neo4j recently wrote, "Dr. Roy Marsten wrote in in March that Graph Theory was a key approach in understanding and leveraging big data. As a advocate of graph theory and as a developer building graph databases since 2003, it was wonderful to read someone else with similar insights and appetites. As Dr. Marsten notes, Google started the graph analysis trend in the modern era using links between documents on the Web to understand their semantic context. As a result, Google produced a Web search engine that massively outperformed its established competitors and saw it jump so far ahead that 'to Google' became a verb. Of course we know very well Google’s history since then: its graph-centric approach has seen it deliver innovation at scale and dominate not only in its core search market, but also across the information management space."
Eifrem continues, "But graphs aren’t just for the likes of Google with virtually limitless funds and armies of Ph.D.’s at their disposal. While Google and its competitors might be content to build their own graph data infrastructure, that technology is also available off the shelf to the rest of us. For example, the Neo4j project is a mature open-source graph database used in production at all kinds of organizations from Global 2000s like Walmart, Lufthansa, and Cisco, to innovative startups like FiftyThree, Medium, and CrunchBase. Graph databases like Neo4j have risen to prominence recently, and as 451 Research analyst Matt Aslett recently observed, are moving out of the general NOSQL umbrella into a category in their own right. They have become popular because like Dr. Marsten, many thousands of other software and data professionals have seen that graphs are the best way of storing and querying their increasingly complex interconnected data."
Image: Courtesy Google