Neo Technology recently announced that Glassdoor, an online jobs and career community, is successfully leveraging its Neo4j solution to offer real-time job recommendations to its large scale job database, which consists of over 20 million members.
The collaboration was ideal because Neo4j's inclination for connected data together with its high-availability clustering technology and cache sharing features will drive Glassdoor's big social graph. This will further help Glassdoor to expand its community and build its brand visibility.
In a statement, Ryan Aylward, SVP and CTO of Glassdoor said "The Neo4j graph database proved the perfect fit for integrating Facebook (News - Alert) into the Glassdoor community. As a result we are able to provide a better experience for our members and provide them with real job recommendations."
Glassdoor was looking for an innovative database that could successfully manage both friends and friends-of-friends information, along with the employer relationships. After completing its research of the market, the company decided that the graph database was the best choice for this connected data set. Neo4j was selected as the database because it had the maturity and feature set that could be used to work alongside its existing technology stack.
Emil Eifrem, CEO of Neo Technology, said, "Glassdoor is the leading online jobs and career community. Glassdoor's innovation in reimagining the job listing business as a social graph search problem is essential to its success at replacing the old static search sites. As the first online job site to let you find jobs through your network of Facebook friends, Glassdoor uses Neo4j to provide real-time job recommendations."
Neo4j offered Glassdoor both the speed and power that was essential to manage its growing database. Now, that there are over 600 million people in the database, and the connections between all of those members, Glassdoor officially has one of the biggest social graphs, providing its members a uniquely large reach. The new collaboration will further enhance the effectiveness and reach of all these members.
Edited by Ryan Sartor