Beyond Macrobenchmarks: Microbenchmark-based Graph Database Evaluation

Matteo Lissandrini, Martin Brugnara, Yannis Velegrakis

    Research output: Contribution to journalArticleAcademicpeer-review

    Abstract

    Despite the increasing interest in graph databases their requirements and specifications are not yet fully understood by everyone, leading to a great deal of variation in the supported functionalities and the achieved performances. In this work, we provide a comprehensive study of the existing graph database systems. We introduce a novel microbenchmarking framework that provides insights on their performance that go beyond what macro-benchmarks can offer. The framework includes the largest set of queries and operators so far considered. The graph database systems are evaluated on synthetic and real data, from different domains, and at scales much larger than any previous work. The framework is materialized as an open-source suite and is easily extended to new datasets, systems, and queries1.

    Original languageEnglish
    Pages (from-to)390-403
    Number of pages14
    JournalProceedings of the VLDB Endowment
    Volume12
    Issue number4
    DOIs
    Publication statusPublished - Dec 2018

    Keywords

    • Benchmark

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