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)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
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}
}Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 43 of 43 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 1,351 | Chimp: Efficient Lossless Floating Point Compression for Time Series Databases | 2022 | VLDB |
| 2 | 11,178 | In-Database Time Series Clustering | 2025 | SIGMOD |
| 3 | 7,198 | Frequency Domain Data Encoding in Apache IoTDB | 2023 | VLDB |
| 4 | 6,712 | MOST: Model-Based Compression with Outlier Storage for Time Series Data | 2023 | SIGMOD |
| 5 | 625 | Efficiently Supporting Ad Hoc Queries in Large Datasets of Time Sequences | 1997 | SIGMOD |
| 6 | 900 | Query Optimization In Compressed Database Systems | 2001 | SIGMOD |
| 7 | 3,634 | Apache IoTDB: A Time Series Database for IoT Applications | 2023 | SIGMOD |
| 8 | 4,880 | Time Series Data Encoding for Efficient Storage: A Comparative Analysis in Apache IoTDB | 2022 | VLDB |
| 9 | 6,737 | CompressDB: Enabling Efficient Compressed Data Direct Processing for Various Databases | 2022 | SIGMOD |
| 10 | 11,640 | On Reducing Space Amplification with Multi-Column Compaction in Apache IoTDB | 2024 | VLDB |