Scaling Semantic Graph Databases in Size and Performance

Alessandro Morari, Vito Giovanni Castellana, Oreste Villa, Antonino Tumeo, Jesse Weaver, David Haglin, Sutanay Choudhury, John Feo

Abstract: GEMS is a full software system that implements a large-scale, semantic graph database on commodity clusters. Its framework comprises a SPARQL-to-C++ compiler, a library of distributed data structures, and a custom multithreaded runtime library. The authors evaluated their software stack on the Berlin SPARQL benchmark with datasets of up to 10 billion graph edges, demonstrating scaling in dataset size and performance as they added cluster nodes.