Wired magazine gives the inside story to Facebook’s Graph Search and some of its challenges. One critical challenge was naming the new product.

In the weeks leading up to the launch, Facebook executives were still trying to come up with a name for the new product. They were hoping to stay away from the word “search,” to distinguish it from web search. (Only a few days before the launch, one Facebook executive slipped and referred to it as “browse.”) But after hours of contortionism, they relented; nothing topped Graph Search. “It’s descriptive — it’s search,” Zuckerberg says. “And the graph is a big thing.” The idea is that Facebook’s new offering will be able to extract meaning from the social graph in much the same way that Google’s original search unearthed the hidden treasures of the web. “People use search engines to answer questions,” Zuckerberg says. “But we can answer a set of questions that no one else can really answer. All those other services are indexing primarily public information, and stuff in Facebook isn’t out there in the world — it’s stuff that people share. There’s no real way to cut through the contents of what people are sharing, to fulfill big human needs about discovery, to find people you wouldn’t otherwise be connected with. And we thought we should do something about that. We’re the only service in the world that can do that.” Read the full article.  

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I think it’s fair to say that Neo4j is by far the most widely deployed graph database in the world. There is hundreds of production systems out there. Being open source we don’t know the details of all of them, but we see lots of uptake in the finance industry, the intelligence community, the GIS/LBS area and in social software. Have a look at the Neo4j in the wild page (http://wiki.neo4j.org/content/Neo4j_In_The_Wild) and our customer list (http://neotechnology.com/customers) to get some ideas of the publicly referencable ones.

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