TVA: A Version-aware Temporal Graph Storage System for Real-time Analytics
Summary: TVA introduces multi-version temporal graph storage that separates version metadata from property data, using temporal tables, hopscotch hashing, and version skipping for efficient neighborhood scans. It cuts temporal-query latency by up to 9.9× and storage overhead by 2.2×. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Wenhao Li (Renmin University of China)
- 2. Zhanhao Zhao (Renmin University of China)
- 3. Jinhao Dong (Renmin University of China)
- 4. Jiamin Hou (Renmin University of China; Zhejiang University)
- 5. Wei Lu (Renmin University of China)
- 6. Yunhai Wang (Renmin University of China)
- 7. Xiaoyong Du (Renmin University of China)
BibTeX Citation
@article{li_vldb26,
title = {{TVA: A Version-aware Temporal Graph Storage System for Real-time Analytics}},
author = {Li, Wenhao and Zhao, Zhanhao and Dong, Jinhao and Hou, Jiamin and Lu, Wei and Wang, Yunhai and Du, Xiaoyong},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {10},
pages = {2536--2548},
doi = {10.14778/3828612.3828613},
url = {https://doi.org/10.14778/3828612.3828613},
year = {2026}
}
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