The LDBC social network benchmark: Interactive workload

Orri Erling, Alex Averbuch, Josep-Lluis Larriba-Pey, Hassan Chafi, Andrey Gubichev, Arnau Prat, Minh Duc Pham, Peter Boncz

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review


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.

Original languageEnglish
Title of host publicationSIGMOD 2015 - Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data
PublisherAssociation for Computing Machinery (ACM)
Number of pages12
ISBN (Electronic)9781450327589
Publication statusPublished - 27 May 2015
EventACM SIGMOD International Conference on Management of Data, SIGMOD 2015 - Melbourne, Australia
Duration: 31 May 20154 Jun 2015


ConferenceACM SIGMOD International Conference on Management of Data, SIGMOD 2015


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