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conference2020ICORE 2026 CCORE 2023 CCCF C

An Empirical Study on Recent Graph Database Systems

Ran Wang, Zhengyi Yang, Wenjie Zhang, Xuemin Lin

International Conference on Knowledge Science, Engineering and Management (KSEM)

RAIDS Lab Authors

Zhengyi Yang
Zhengyi Yang
Director

Details

Year
2020
Venue
International Conference on Knowledge Science, Engineering and Management (KSEM)
Publisher
Springer
Rankings
ICORE 2026 C · CORE 2023 C · CCF C

Research Area

Scalable Data Systems

Tags

GraphDatabaseBenchmarkSystems

Resources

Code ↗DOI ↗

Awards

Best Student Paper Award

Abstract

Graphs are widely used to model the intricate relationships among objects in a wide range of applications. The advance in graph data has brought significant value to artificial intelligence technologies. Recently, a number of graph database systems have been developed. In this paper, we present a comprehensive overview and empirical investigation on existing property graph database systems such as Neo4j, AgensGraph, TigerGraph and LightGraph (LightGraph has recently renamed to TuGraph.). These systems support declarative graph query languages. Our empirical studies are conducted in a single-machine environment against on the LDBC social network benchmark, consisting of three different large-scale datasets and a set of benchmark queries. This is the first empirical study to compare these graph database systems by evaluating data bulk importing and processing simple and complex queries. Experimental results provide insightful observations of various graph data systems and indicate that AgensGraph works well on SQL based workload and simple update queries, TigerGraph is powerful on complex business intelligence queries, Neo4j is user-friendly and suitable for small queries, and LightGraph is a more balanced product achieving good performance on different queries. The related code, scripts and data of this paper are available online (https://github.com/UNSW-database/GraphDB-Benchmark).

Author Affiliations

Ran Wang
East China Normal University
Zhengyi Yang
University of New South Wales
Wenjie Zhang
University of New South Wales
Xuemin Lin
University of New South Wales

BibTeX

@inproceedings{wang2020empirical,
  title = {An Empirical Study on Recent Graph Database Systems},
  author = {Wang, Ran and Yang, Zhengyi and Zhang, Wenjie and Lin, Xuemin},
  editor = {Li, Gang and Shen, Heng Tao and Yuan, Ye and Wang, Xiaoyang and Liu, Huawen and Zhao, Xiang},
  booktitle = {Knowledge Science, Engineering and Management},
  year = {2020},
  publisher = {Springer International Publishing},
  address = {Cham},
  pages = {328--340},
  isbn = {978-3-030-55130-8}
}