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The LDBC Graphalytics Benchmark

30 November 2020
Alexandru Iosup
Ahmed Musaafir
Alexandru Uta
Arnau Prat-Pérez
Gábor Szárnyas
Hassan Chafi
Ilie Gabriel Tanase
Lifeng Nai
Michael J. Anderson
Mihai Capota
N. Sundaram
P. Boncz
Siegfried Depner
Stijn Heldens
Thomas Manhardt
T. Hegeman
W. L. Ngai
Yinglong Xia
ArXiv (abs)PDFHTML
Abstract

In this document, we describe LDBC Graphalytics, an industrial-grade benchmark for graph analysis platforms. The main goal of Graphalytics is to enable the fair and objective comparison of graph analysis platforms. Due to the diversity of bottlenecks and performance issues such platforms need to address, Graphalytics consists of a set of selected deterministic algorithms for full-graph analysis, standard graph datasets, synthetic dataset generators, and reference output for validation purposes. Its test harness produces deep metrics that quantify multiple kinds of systems scalability, weak and strong, and robustness, such as failures and performance variability. The benchmark also balances comprehensiveness with runtime necessary to obtain the deep metrics. The benchmark comes with open-source software for generating performance data, for validating algorithm results, for monitoring and sharing performance data, and for obtaining the final benchmark result as a standard performance report.

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