Improving Time Series Data Compression in Apache IoTDB
Summary: Introduces homomorphic compression theory for time-series queries and CompressIoTDB, an Apache IoTDB integration using CompColumn to support filtering, aggregation, and windows without decompression. Late decompression and dynamic auxiliary management yield 53.4% higher throughput and 20% lower memory. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Yuxin Tang (Renmin University of China)
- 2. Feng Zhang (Renmin University of China)
- 3. Jiawei Guan (Renmin University of China)
- 4. Yuan Tian (Timecho)
- 5. Xiangdong Huang (Tsinghua University)
- 6. Chen Wang (Tsinghua University)
- 7. Jianmin Wang (Tsinghua University)
- 8. Xiaoyong Du (Renmin University of China)
BibTeX Citation
@article{tang_vldb25,
title = {{Improving Time Series Data Compression in Apache IoTDB}},
author = {Tang, Yuxin and Zhang, Feng and Guan, Jiawei and Tian, Yuan and Huang, Xiangdong and Wang, Chen and Wang, Jianmin and Du, Xiaoyong},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {10},
pages = {3406--3420},
doi = {10.14778/3748191.3748204},
url = {https://doi.org/10.14778/3748191.3748204},
year = {2025}
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