Maxdemarzi/neography. And Ruby. Max De Marzi | Ruby + Graphs with Neo4j. Ranking - popularity ranking of database management systems. 50 Shades of Graph: How Graph Databases Are Transforming Online Dating. Using set cover algorithm to optimize query latency for a large scale distributed graph. Social networks often require the ability to perform low latency graph computations in the user request path. For example, at LinkedIn, we show the graph distance and common connections whenever we show a profile on the site. To do this, we have developed a distributed and partitioned graph system that scales to hundreds of millions of members and their connections and handles hundreds of thousands of queries per second. We published a paper in the HotCloud'13 Conference, June 2013 that describes one of the techniques we use to keep latencies low: Using Set Cover to Optimize a Large-Scale Low Latency Distributed Graph In this post, I'll describe the greedy set cover algorithm we developed and how it reduces latencies for more than half the queries in our real-time distributed graph infrastructure.
Overview of Query Routing LinkedIn's distributed graph system consists of three major subcomponents: GraphDB: a partitioned and replicated graph database. Graph Architecture Distance Icons. Neo4j.