Beyond Macrobenchmarks: Microbenchmark-based Graph Database Evaluation

Matteo Lissandrini, Martin Brugnara, Yannis Velegrakis

Research output: Contribution to journalJournal articleResearchpeer-review

29 Citations (Scopus)
348 Downloads (Pure)


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
JournalProceedings of the VLDB Endowment
Issue number4
Pages (from-to)390-403
Publication statusPublished - 2018
Event45th International Conference on Very Large Data Bases -
Duration: 26 Aug 201930 Aug 2019
Conference number: 45


Conference45th International Conference on Very Large Data Bases
Internet address


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