Article originally posted on Fierce Data
Graph-based search has pretty much been the province of giants like Facebook and Google, who use it to manage huge volumes of content and make data available in real-time to users. The makers of Neo4j, a graph database used by companies such as Walmart, eBay, HP and Cisco, said that more firms of all sizes are beginning to take hold of graph-based search as the technology inches its way to mainstream use.
Neo4j has been around for over a decade so this is no startup looking for an angel investor. And graph-based search was actually made famous by Google and Facebook, so you know this is no trendy, hope-it-works tech.
Like most big data tech and analytics in use in business spheres of all shapes and sizes today, it was put through its paces by the big boys first.
Only you know what tech works best for you though, so don’t take this post as an endorsement. Rather I’m explaining from whence it came and to where it is going. At the moment it appears to be on path to much wider use, and for all the right reasons. Indeed, several industry analysts and leaders have predicted for years that semantic and graph-based search were the future of search and those predictions appear to be coming true.
“It’s impossible for traditional relational databases and keyword-based searches to keep up with the crush of big data. That is why companies have turned to graphs,” said Emil Eifrem, founder and CEO of Neo Technology, the makers of Neo4j in a prepared statement. “For businesses that have huge volumes of content, graph-based search provides the best possible way to make this data available to users, as Google and Facebook have both demonstrated.”
While graph-based search delivers many benefits in most cases, perhaps the most compelling is the ability to respond to customers in real-time.
“The real difference compared to a relational database is that we can give people an answer within their lifetime – because sometimes you’d have to wait a full minute or two minutes, and two minutes in the world of computers is an eternity, so that’s just as bad as not answering them,” said Evan Stein, founder of Decibel, a company that offers detailed data on over one million albums of every type of music to users. “Graph-based search makes things possible that we only dreamed of before.”
If you would like to learn more about graph-based search, you might want to check out Neo4j’s white paper [reg. req.] on the subject. You might also want to check out the post in MPO on Seven Bridges’ work in developing a graph-based genome tool to get an idea of how far-reaching and varied the graph approach is in big data efforts.
Keywords: emil eifrem • fierce big data • graph-based search