High-Ratio Compression for Machine-Generated Data
Summary: Pattern-Based Compression (PBC) exploits patterns in machine-generated data to achieve Pareto-optimal compression. Per-record encoding enables fast random access, delivering ~2× ratios over state-of-the-art with production-ready deployment in DB systems. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jiujing Zhang (Guangdong University of Technology; University of New South Wales)
- 2. Zhitao Shen (Ant Financial)
- 3. Shiyu Yang (Guangdong University of Technology)
- 4. Lingkai Meng (Ant Financial; Shanghai Jiao Tong University)
- 5. Chuan Xiao (Nagoya University; Osaka University)
- 6. Wei Jia (Ant Financial)
- 7. Yue Li (Ant Financial)
- 8. Qinhui Sun (Ant Financial)
- 9. Wenjie Zhang (University of New South Wales)
- 10. Xuemin Lin (Shanghai Jiao Tong University)
BibTeX Citation
@inproceedings{zhang_sigmod23,
title = {{High-Ratio Compression for Machine-Generated Data}},
author = {Zhang, Jiujing and Shen, Zhitao and Yang, Shiyu and Meng, Lingkai and Xiao, Chuan and Jia, Wei and Li, Yue and Sun, Qinhui and Zhang, Wenjie and Lin, Xuemin},
series = {{SIGMOD} '23},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3626732},
url = {https://dl.acm.org/doi/10.1145/3626732},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,038 | The FastLanes File Format | 2025 | VLDB | 5.3270943e-05 |
| 10,589 | Morphing-based Compression for Data-centric ML Pipelines | 2026 | VLDB | 5.093636e-05 |
| 10,946 | LogLite: Lightweight Plug-and-Play Streaming Log Compression | 2025 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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