Beyond Macrobenchmarks: Microbenchmark-based Graph Database Evaluation

Matteo Lissandrini, Martin Brugnara, Yannis Velegrakis

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

15 Citationer (Scopus)
281 Downloads (Pure)

Abstrakt

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
.
OriginalsprogEngelsk
TidsskriftProceedings of the VLDB Endowment
Vol/bind12
Udgave nummer4
Sider (fra-til)390-403
ISSN2150-8097
DOI
StatusUdgivet - 2018
Begivenhed45th International Conference on Very Large Data Bases -
Varighed: 26 aug. 201930 aug. 2019
Konferencens nummer: 45
http://vldb.org/2019/

Konference

Konference45th International Conference on Very Large Data Bases
Nummer45
Periode26/08/201930/08/2019
Internetadresse

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  • EXQ: Exemplar Query Search

    Lissandrini, M.

    01/01/2014 → …

    Projekter: ProjektForskning

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