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).

Information on the talk:

• Expected prior knowledge: specialized prior knowledge is not needed
• Intended audience: developers and users of graph database management systems

Speakers:

• Gábor Szárnyas is a post-doctoral researcher at CWI Amsterdam. He is the lead developer of the LDBC Social Network Benchmark's BI workload and the maintainer of the Graphalytics benchmark. He is a member of the LDBC steering committee.
• David Püroja is a research software engineer at CWI Amsterdam and the maintainer of the LDBC Social Network Benchmark's Interactive workload. He is a certified LDBC auditor.

Previous talks:

• The LDBC Social Network Benchmark: Business Intelligence workload (15th LDBC Technical User Community meeting, 2022)
• The Linked Data Benchmark Council: Fostering competition in the graph processing space (World AI Conference, 2022)