The Linked Data Benchmark Council (LDBC) is now two years underway and has gathered strong industrial participation for its mission to establish benchmarks, and benchmarking practices for evaluating graph data management systems. The LDBC introduced a new choke-point driven methodology for developing benchmark workloads, which combines user input with input from expert systems architects, which we outline. This paper describes the LDBC Social Network Benchmark (SNB), and presents database benchmarking innovation in terms of graph query functionality tested, correlated graph generation techniques, as well as a scalable benchmark driver on a workload with complex graph dependencies. SNB has three query workloads under development: Interactive, Business Intelligence, and Graph Algorithms. We describe the SNB Interactive Workload in detail and illustrate the workload with some early results, as well as the goals for the two other workloads.
Additional Metadata
Keywords RDF benchmark, LDBC, Social network benchmark
THEME Information (theme 2)
Stakeholder Unspecified
Conference ACM SIGMOD International Conference on Management of Data
Citation
Erling, O, Averbuch, A, Larriba-Pey, J, Chafi, H, Gubichev, A, Prat, A, … Boncz, P.A. (2015). The LDBC Social Network Benchmark: Interactive Workload. In Proceedings of ACM SIGMOD International Conference on Management of Data 2015 (SIGMOD'15).

Additional Files
23380B.pdf Author Manuscript , 698kb