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Autores principales: Hao, Chiyu, Su, Jixian, Sun, Shixuan, Zhang, Hao, Gao, Sen, Zhao, Jianwen, Zhang, Chenyi, Zhao, Jieru, Chen, Chen, Guo, Minyi
Formato: Preprint
Publicado: 2025
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Acceso en línea:https://arxiv.org/abs/2507.00839
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author Hao, Chiyu
Su, Jixian
Sun, Shixuan
Zhang, Hao
Gao, Sen
Zhao, Jianwen
Zhang, Chenyi
Zhao, Jieru
Chen, Chen
Guo, Minyi
author_facet Hao, Chiyu
Su, Jixian
Sun, Shixuan
Zhang, Hao
Gao, Sen
Zhao, Jianwen
Zhang, Chenyi
Zhao, Jieru
Chen, Chen
Guo, Minyi
contents Dynamic graph storage systems are essential for real-time applications such as social networks and recommendation, where graph data continuously evolves. However, they face significant challenges in efficiently handling concurrent read and write operations. We find that existing methods suffer from write queries interfering with read efficiency, substantial time and space overhead due to per-edge versioning, and an inability to balance performance, such as slow searches under concurrent workloads. To address these issues, we propose RapidStore, a holistic approach for efficient in-memory dynamic graph storage designed for read-intensive workloads. Our key idea is to exploit the characteristics of graph queries through a decoupled system design that separates the management of read and write queries and decouples version data from graph data. Particularly, we design an efficient dynamic graph store to cooperate with the graph concurrency control mechanism. Experimental results demonstrate that RapidStore enables fast and scalable concurrent graph queries, effectively balancing the performance of inserts, searches, and scans, and significantly improving efficiency in dynamic graph storage systems.
format Preprint
id arxiv_https___arxiv_org_abs_2507_00839
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle RapidStore: An Efficient Dynamic Graph Storage System for Concurrent Queries
Hao, Chiyu
Su, Jixian
Sun, Shixuan
Zhang, Hao
Gao, Sen
Zhao, Jianwen
Zhang, Chenyi
Zhao, Jieru
Chen, Chen
Guo, Minyi
Databases
Dynamic graph storage systems are essential for real-time applications such as social networks and recommendation, where graph data continuously evolves. However, they face significant challenges in efficiently handling concurrent read and write operations. We find that existing methods suffer from write queries interfering with read efficiency, substantial time and space overhead due to per-edge versioning, and an inability to balance performance, such as slow searches under concurrent workloads. To address these issues, we propose RapidStore, a holistic approach for efficient in-memory dynamic graph storage designed for read-intensive workloads. Our key idea is to exploit the characteristics of graph queries through a decoupled system design that separates the management of read and write queries and decouples version data from graph data. Particularly, we design an efficient dynamic graph store to cooperate with the graph concurrency control mechanism. Experimental results demonstrate that RapidStore enables fast and scalable concurrent graph queries, effectively balancing the performance of inserts, searches, and scans, and significantly improving efficiency in dynamic graph storage systems.
title RapidStore: An Efficient Dynamic Graph Storage System for Concurrent Queries
topic Databases
url https://arxiv.org/abs/2507.00839