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Link to original content: https://doi.org/10.48550/arXiv.2307.04350
[2307.04350] The Linked Data Benchmark Council (LDBC): Driving competition and collaboration in the graph data management space
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Computer Science > Databases

arXiv:2307.04350 (cs)
[Submitted on 10 Jul 2023 (v1), last revised 30 Aug 2024 (this version, v3)]

Title:The Linked Data Benchmark Council (LDBC): Driving competition and collaboration in the graph data management space

Authors:Gábor Szárnyas, Brad Bebee, Altan Birler, Alin Deutsch, George Fletcher, Henry A. Gabb, Denise Gosnell, Alastair Green, Zhihui Guo, Keith W. Hare, Jan Hidders, Alexandru Iosup, Atanas Kiryakov, Tomas Kovatchev, Xinsheng Li, Leonid Libkin, Heng Lin, Xiaojian Luo, Arnau Prat-Pérez, David Püroja, Shipeng Qi, Oskar van Rest, Benjamin A. Steer, Dávid Szakállas, Bing Tong, Jack Waudby, Mingxi Wu, Bin Yang, Wenyuan Yu, Chen Zhang, Jason Zhang, Yan Zhou, Peter Boncz
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Abstract:Graph data management is instrumental for several use cases such as recommendation, root cause analysis, financial fraud detection, and enterprise knowledge representation. Efficiently supporting these use cases yields a number of unique requirements, including the need for a concise query language and graph-aware query optimization techniques. The goal of the Linked Data Benchmark Council (LDBC) is to design a set of standard benchmarks that capture representative categories of graph data management problems, making the performance of systems comparable and facilitating competition among vendors. LDBC also conducts research on graph schemas and graph query languages. This paper introduces the LDBC organization and its work over the last decade.
Subjects: Databases (cs.DB)
ACM classes: H.2.4
Cite as: arXiv:2307.04350 [cs.DB]
  (or arXiv:2307.04350v3 [cs.DB] for this version)
  https://doi.org/10.48550/arXiv.2307.04350

Submission history

From: Gábor Szárnyas [view email]
[v1] Mon, 10 Jul 2023 05:20:36 UTC (109 KB)
[v2] Thu, 17 Aug 2023 08:27:55 UTC (115 KB)
[v3] Fri, 30 Aug 2024 11:30:26 UTC (115 KB)
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