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Lindorm-UWC: An Ultra-Wide-Column Database for Internet of Vehicles

Summary: Empirical study of real-world IoV workloads reveals extreme high-throughput, multi-metric writes that challenge conventional DBMS designs. Lindorm-UWC uses per-partition ultra-wide-column storage with cold/hot separation to handle multi-metric ingestion, achieving ~79% higher write throughput, competitive query performance, and tens of PB in production. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13799
Venue
VLDB
Year
2024
Pagerank
5.093636e-05
Overall Rank
11,294 | 22.52%
DOI
10.14778/3685800.3685831

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Authors

BibTeX Citation

@article{ouyang_vldb24,
        title = {{Lindorm-UWC: An Ultra-Wide-Column Database for Internet of Vehicles}},
        author = {Ouyang, Qianyu and Shen, Chunhui and Yang, Wenlong and Yu, Peng and Xiao, Qiang and Lei, Jianhui and Chen, Yadong and Zhong, Qilu and Wang, Xiang and Lin, Yong and Meng, Qingyi and Ji, Zhicheng and Meng, Wei and Zheng, Cen and Wang, Sheng and Pei, Dan and Zhang, Wei and Li, Feifei and Zhou, Jingren},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {12},
        pages = {4117--4129},
        doi = {10.14778/3685800.3685831},
        url = {https://doi.org/10.14778/3685800.3685831},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

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Rank Citing Paper Year Venue Pagerank
10,258 Kangaroo: Efficient Lossless Floating-Point Compression via Dynamic Reference Selection 2026 SIGMOD 5.093636e-05
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