Title :
Scaling Semantic Graph Databases in Size and Performance
Author :
Morari, Alessandro ; Castellana, Vito Giovanni ; Villa, Oreste ; Tumeo, Antonino ; Weaver, James ; Haglin, David ; Choudhury, Sankhayan ; Feo, John
Author_Institution :
Pacific Northwest Nat. Lab., Richland, WA, USA
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.
Keywords :
data structures; multi-threading; program compilers; software libraries; very large databases; workstation clusters; Berlin SPARQL benchmark; GEMS; SPARQL-to-C++ compiler; commodity clusters; distributed data structure library; large-scale semantic graph database; multithreaded runtime library; performance scaling; size scaling; software stack; Big data; Cluster approximation; Data structures; Distributed processing; Multithreading; Resource description framework; Runtime; Semantics; SPARQL; big data; cluster; data aggregation; data analysis; distributed systems; graph databases; multithreading;
Journal_Title :
Micro, IEEE
