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An Experimental Comparison of RDF Systems on Cloud

Yi Ding, Hualong Lin, Zhengyi Yang*, Dong Wen, Xiaoyang Wang, Wenjie Zhang

Australasian Database Conference (ADC)

RAIDS Lab Authors

Zhengyi Yang
Zhengyi Yang
(corresponding author)
Director

Details

Year
2024
Venue
Australasian Database Conference (ADC)
Publisher
Springer
Rankings
ICORE 2026 Australasian B · CORE 2023 Australasian B

Research Area

Scalable Data Systems

Tags

RDFBenchmarkSystems

Resources

DOI ↗

Abstract

With the growing use of graph-based applications across various domains, the demand for efficient and scalable RDF (Resource Description Framework) systems has intensified. As organizations increasingly deploy RDF systems on cloud infrastructures, understanding the trade-offs between performance and cost becomes critical. This paper presents a comprehensive experimental comparison of multiple RDF systems, analyzing their performance in cloud and on-premises environments. Our study evaluates key metrics such as query execution time, data ingestion speed, storage efficiency, and cost-effectiveness across several benchmarks, including LDBC SNB, WatDiv, LUBM, and DBpedia. The experiments reveal distinct advantages and limitations in RDF systems. Notably, Virtuoso demonstrated strong performance and cost-efficiency across most datasets, while systems like gStore exhibited higher variability under stress conditions. Our findings offer actionable insights for practitioners seeking to balance performance and cost when deploying RDF systems in cloud environments. We also highlight areas for improvement in system documentation, compatibility, and stability under extreme workloads. Future work will explore alternative architectures and further optimization strategies for cloud-based RDF solutions. The related code, scripts and data of this paper are available online (https://github.com/unswdb/RDF_on_Cloud).

Author Affiliations

Yi Ding
Euler AI
Hualong Lin
Sigma Trading Management Pty Ltd.
Zhengyi Yang
University of New South Wales
Dong Wen
University of New South Wales
Xiaoyang Wang
University of New South Wales
Wenjie Zhang
University of New South Wales

BibTeX

@inproceedings{ding2024benchmarking,
  title = {An Experimental Comparison of RDF Systems on Cloud},
  author = {Ding, Yi and Lin, Hualong and Yang, Zhengyi and Wen, Dong and Wang, Xiaoyang and Zhang, Wenjie},
  editor = {Chen, Tong and Cao, Yang and Nguyen, Quoc Viet Hung and Nguyen, Thanh Tam},
  booktitle = {Databases Theory and Applications},
  year = {2025},
  publisher = {Springer Nature Singapore},
  address = {Singapore},
  pages = {30--43},
  isbn = {978-981-96-1242-0}
}