The Linked Data Benchmark Council (LDBC): Driving Competition and Collaboration in the Graph Data Management Space

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

doi:10.1007/978-3-031-68031-1_7

The Linked Data Benchmark Council (LDBC): Driving Competition and Collaboration in the Graph Data Management Space

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 PürojaShipeng 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

^*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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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.

Original language	English
Title of host publication	Performance Evaluation and Benchmarking
Subtitle of host publication	15th TPC Technology Conference, TPCTC 2023, Vancouver, BC, Canada, August 28 – September 1, 2023, Revised Selected Papers
Editors	Raghunath Nambiar, Meikel Poess
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	90-106
Number of pages	17
ISBN (Electronic)	9783031680311
ISBN (Print)	9783031680304
DOIs	https://doi.org/10.1007/978-3-031-68031-1_7
Publication status	Published - 2024
Event	15th TPC Technology Conference on Performance Evaluation and Benchmarking, TPCTC 2023, held concurrently with the 49th International Conference on Very Large Data Bases, VLDB 2023 - Vancouver, Canada Duration: 28 Aug 2023 → 1 Sept 2023

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	14247 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Name	TPCTC: Technology Conference on Performance Evaluation and Benchmarking
Publisher	Springer
Volume	2023

Conference

Conference	15th TPC Technology Conference on Performance Evaluation and Benchmarking, TPCTC 2023, held concurrently with the 49th International Conference on Very Large Data Bases, VLDB 2023
Country/Territory	Canada
City	Vancouver
Period	28/08/23 → 1/09/23

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Access to Document

10.1007/978-3-031-68031-1_7

The Linked Data Benchmark Council (LDBC)_Driving Competition and Collaboration in the Graph Data Management SpaceFinal published version, 370 KBLicence: Article 25fa Dutch Copyright Act

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Cite this

Szárnyas, G., Bebee, B., Birler, A., Deutsch, A., Fletcher, G., Gabb, H. A., Gosnell, D., Green, A., Guo, Z., Hare, K. W., Hidders, J., Iosup, A., Kiryakov, A., Kovatchev, T., Li, X., Libkin, L., Lin, H., Luo, X., Prat-Pérez, A., ... Boncz, P. (2024). The Linked Data Benchmark Council (LDBC): Driving Competition and Collaboration in the Graph Data Management Space. In R. Nambiar, & M. Poess (Eds.), Performance Evaluation and Benchmarking: 15th TPC Technology Conference, TPCTC 2023, Vancouver, BC, Canada, August 28 – September 1, 2023, Revised Selected Papers (pp. 90-106). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14247 LNCS), (TPCTC: Technology Conference on Performance Evaluation and Benchmarking; Vol. 2023). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-68031-1_7

Szárnyas, Gábor ; Bebee, Brad ; Birler, Altan et al. / The Linked Data Benchmark Council (LDBC) : Driving Competition and Collaboration in the Graph Data Management Space. Performance Evaluation and Benchmarking: 15th TPC Technology Conference, TPCTC 2023, Vancouver, BC, Canada, August 28 – September 1, 2023, Revised Selected Papers. editor / Raghunath Nambiar ; Meikel Poess. Springer Science and Business Media Deutschland GmbH, 2024. pp. 90-106 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). (TPCTC: Technology Conference on Performance Evaluation and Benchmarking).

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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.",

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Szárnyas, G, Bebee, B, Birler, A, Deutsch, A, Fletcher, G, Gabb, HA, Gosnell, D, Green, A, Guo, Z, Hare, KW, Hidders, J, Iosup, A, Kiryakov, A, Kovatchev, T, Li, X, Libkin, L, Lin, H, Luo, X, Prat-Pérez, A, Püroja, D, Qi, S, van Rest, O, Steer, BA, Szakállas, D, Tong, B, Waudby, J, Wu, M, Yang, B, Yu, W, Zhang, C, Zhang, J, Zhou, Y & Boncz, P 2024, The Linked Data Benchmark Council (LDBC): Driving Competition and Collaboration in the Graph Data Management Space. in R Nambiar & M Poess (eds), Performance Evaluation and Benchmarking: 15th TPC Technology Conference, TPCTC 2023, Vancouver, BC, Canada, August 28 – September 1, 2023, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14247 LNCS, TPCTC: Technology Conference on Performance Evaluation and Benchmarking, vol. 2023, Springer Science and Business Media Deutschland GmbH, pp. 90-106, 15th TPC Technology Conference on Performance Evaluation and Benchmarking, TPCTC 2023, held concurrently with the 49th International Conference on Very Large Data Bases, VLDB 2023, Vancouver, Canada, 28/08/23. https://doi.org/10.1007/978-3-031-68031-1_7

The Linked Data Benchmark Council (LDBC): Driving Competition and Collaboration in the Graph Data Management Space. / Szárnyas, Gábor; Bebee, Brad; Birler, Altan et al.
Performance Evaluation and Benchmarking: 15th TPC Technology Conference, TPCTC 2023, Vancouver, BC, Canada, August 28 – September 1, 2023, Revised Selected Papers. ed. / Raghunath Nambiar; Meikel Poess. Springer Science and Business Media Deutschland GmbH, 2024. p. 90-106 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14247 LNCS), (TPCTC: Technology Conference on Performance Evaluation and Benchmarking; Vol. 2023).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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AU - Prat-Pérez, Arnau

AU - Püroja, David

AU - Qi, Shipeng

AU - van Rest, Oskar

AU - Steer, Benjamin A.

AU - Szakállas, Dávid

AU - Tong, Bing

AU - Waudby, Jack

AU - Wu, Mingxi

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AU - Zhou, Yan

AU - Boncz, Peter

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AB - 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.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Szárnyas G, Bebee B, Birler A, Deutsch A, Fletcher G, Gabb HA et al. The Linked Data Benchmark Council (LDBC): Driving Competition and Collaboration in the Graph Data Management Space. In Nambiar R, Poess M, editors, Performance Evaluation and Benchmarking: 15th TPC Technology Conference, TPCTC 2023, Vancouver, BC, Canada, August 28 – September 1, 2023, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2024. p. 90-106. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). (TPCTC: Technology Conference on Performance Evaluation and Benchmarking). Epub 2024 Sept 22. doi: 10.1007/978-3-031-68031-1_7