In this talk, we describe the LDBC Social Network Benchmark's two workloads: the Interactive workload for transactional graph database systems and the Business Intelligence workload for analytical graph data systems.
The Linked Data Benchmark Council (LDBC) was founded in 2012 by vendors and academic researchers with the aim of making graph processing performance measurable and comparable. To this end, LDBC provides open-source benchmark suites with openly available data sets starting at 1 GB and scaling up to 30 TB. Additionally, it allows vendors to submit their benchmark implementations to LDBC-certified auditors who ensure that the benchmark executions are reproducible and comply with the specification.
We describe the key features of both workloads, including their data sets, queries, and update operations. We explain how they ensure meaningful and interpretable results via careful parameter tuning. Finally, we showcase the workloads' reference implementations (maintained by vendors and community members).
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Speakers: Gabor Szarnyas David Püroja