research-article

The LDBC Social Network Benchmark: Interactive Workload

Authors:

Josep Larriba-Pey,

Andrey Gubichev,

Peter BonczAuthors Info & Claims

SIGMOD '15: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data

Pages 619 - 630

https://doi.org/10.1145/2723372.2742786

Published: 27 May 2015 Publication History

Abstract

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.

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Cited By

Sharma CGenevès PGesbert NLayaïda N(2025)Schema-Based Query Optimisation for Graph DatabasesProceedings of the ACM on Management of Data10.1145/37097223:1(1-29)Online publication date: 11-Feb-2025
https://dl.acm.org/doi/10.1145/3709722
Su JHao CSun SZhang HGao SJiang JChen YZhang CHe BGuo M(2025)Revisiting the Design of In-Memory Dynamic Graph StorageProceedings of the ACM on Management of Data10.1145/37097203:1(1-27)Online publication date: 11-Feb-2025
https://dl.acm.org/doi/10.1145/3709720
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Index Terms

The LDBC Social Network Benchmark: Interactive Workload
1. Information systems
  1. Data management systems

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Published In

cover image ACM Conferences

SIGMOD '15: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data

May 2015

2110 pages

ISBN:9781450327589

DOI:10.1145/2723372

General Chair:
Timos Sellis
RMIT University, Australia
,
Program Chairs:
Susan B. Davidson
University of Pennsylvania, USA
,
Zack Ives
University of Pennsylvania, USA

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMOD: ACM Special Interest Group on Management of Data

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 May 2015

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SIGMOD/PODS'15

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SIGMOD

SIGMOD/PODS'15: International Conference on Management of Data

May 31 - June 4, 2015

Victoria, Melbourne, Australia

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SIGMOD '15 Paper Acceptance Rate 106 of 415 submissions, 26%;

Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

Sharma CGenevès PGesbert NLayaïda N(2025)Schema-Based Query Optimisation for Graph DatabasesProceedings of the ACM on Management of Data10.1145/37097223:1(1-29)Online publication date: 11-Feb-2025
https://dl.acm.org/doi/10.1145/3709722
Su JHao CSun SZhang HGao SJiang JChen YZhang CHe BGuo M(2025)Revisiting the Design of In-Memory Dynamic Graph StorageProceedings of the ACM on Management of Data10.1145/37097203:1(1-27)Online publication date: 11-Feb-2025
https://dl.acm.org/doi/10.1145/3709720
Xia YFang YLuo W(2025)Efficiently Counting Triangles in Large Temporal GraphsProceedings of the ACM on Management of Data10.1145/37096883:1(1-27)Online publication date: 11-Feb-2025
https://dl.acm.org/doi/10.1145/3709688
Lv ZWang LLiu YZhao KPeng Y(2025)CIGraph: Accelerating Graph Queries over Database with Compressed IndexAlgorithms and Architectures for Parallel Processing10.1007/978-981-96-1548-3_13(192-202)Online publication date: 17-Feb-2025
https://doi.org/10.1007/978-981-96-1548-3_13
Sandhya Rani AAshwitha GSwarupa Rani K(2025)SDG_HHAG Framework: Homogeneous and Heterogeneous Attributed GraphsBig Data and Artificial Intelligence10.1007/978-3-031-81821-9_6(92-112)Online publication date: 4-Mar-2025
https://doi.org/10.1007/978-3-031-81821-9_6
Hanski JTaelman RVerborgh R(2025)Observations on Bloom Filters for Traversal-Based Query Execution over Solid PodsThe Semantic Web: ESWC 2024 Satellite Events10.1007/978-3-031-78952-6_32(228-233)Online publication date: 28-Jan-2025
https://doi.org/10.1007/978-3-031-78952-6_32
Lee GPark JKim M(2024)Chimera: A System Design of Dual Storage and Traversal-Join Unified Query Processing for SQL/PGQProceedings of the VLDB Endowment10.14778/3705829.370584518:2(279-292)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.14778/3705829.3705845
Hajidehi MSridhar SSeltzer M(2024)CUTTANA: Scalable Graph Partitioning for Faster Distributed Graph Databases and AnalyticsProceedings of the VLDB Endowment10.14778/3696435.369643718:1(14-27)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.14778/3696435.3696437
Tong BZhou YZhang CTang JTang JYang LLi QLin MBao ZLi JChen L(2024)Galaxybase: A High Performance Native Distributed Graph Database for HTAPProceedings of the VLDB Endowment10.14778/3685800.368581417:12(3893-3905)Online publication date: 8-Nov-2024
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Gou XYe XZou LYu J(2024)LM-SRPQ: Efficiently Answering Regular Path Query in Streaming GraphsProceedings of the VLDB Endowment10.14778/3641204.364121417:5(1047-1059)Online publication date: 1-Jan-2024
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