Beyond Macrobenchmarks: Microbenchmark-based Graph Database Evaluation

Matteo Lissandrini, Martin Brugnara, Yannis Velegrakis

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The final authenticated version is available online at 10.14778/3297753.3297759.

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. We provide a comprehensive study of the existing graph database systems. We introduce a novel micro-benchmarking framework that provides insights on their performance that go beyond what macro-benchmarks can offer. We have identified and included in our framework the largest set of queries and operators, we have evaluated the systems on both synthetic and real data, from different domains, and at much larger scales of any previous work. We materialized our evaluation framework in an open-source suite that can be easily extended with new datasets, systems, or queries.

Cite:

and
“Beyond Macrobenchmarks: Microbenchmark-based Graph Database Evaluation.”
Proceedings of the VLDB Endowment 12 , (4) (): 390-403. 

@article{Lissandrini:2018:GDB,
 author = {Lissandrini, Matteo and Brugnara, Martin and Velegrakis, Yannis},
 title = {Beyond Macrobenchmarks: Microbenchmark-based Graph Database Evaluation},
 journal = {PVLDB},
 issue_date = {December 2018},
 volume = {12},
 number = {4},
 month = dec,
 year = {2018},
 pages = {390–-403},
 numpages = {14},
 url = {https://doi.org/10.14778/3297753.3297759},
 doi = {10.14778/3297753.3297759},
 publisher = {VLDB Endowment}
}