Building a High-Performance Graph Storage on Top of Tree-Structured Key-Value Stores

作     者：Heng Lin Zhiyong Wang Shipeng Qi Xiaowei Zhu Chuntao Hong Wenguang Chen Yingwei Luo 

作者机构：School of Computer SciencePeking UniversityBeijing 100871China Ant GroupBeijing 100020China Department of Computer Science and TechnologyTsinghua UniversityBeijing 100084China 

出 版 物：《Big Data Mining and Analytics》 (大数据挖掘与分析（英文）)

年 卷 期：2024年第7卷第1期

页      面：156-170页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 

主　　题：graph database high-performance graph storage 

摘      要：Graph databases have gained widespread adoption in various industries and have been utilized in a range of applications,including financial risk assessment,commodity recommendation,and data lineage *** the principles and design of these databases have been the subject of some investigation,there remains a lack of comprehensive examination of aspects such as storage layout,query language,and *** present study focuses on the design and implementation of graph storage layout,with a particular emphasis on tree-structured key-value *** also examine different design choices in the graph storage layer and present our findings through the development of TuGraph,a highly efficient single-machine graph database that significantly outperforms well-known Graph DataBase Management System(GDBMS).Additionally,TuGraph demonstrates superior performance in the Linked Data Benchmark Council(LDBC)Social Network Benchmark(SNB)interactive benchmark.