An Evaluation of Methods of Compressing Doubles
Summary: Empirical comparison of double-precision compression methods across real-world data: time series, featurized ML data, and machine logs. Comparative focus on compression ratio and throughput, revealing dataset-driven tradeoffs for data-management workloads. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Jacob Spiegel (University of Chicago)
BibTeX Citation
@inproceedings{spiegel_sigmod20,
title = {{An Evaluation of Methods of Compressing Doubles}},
author = {Spiegel, Jacob},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3384415},
url = {https://dl.acm.org/doi/10.1145/3318464.3384415},
year = {2020}
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 148 | Gorilla: A Fast, Scalable, In-Memory Time Series Database | 2015 | VLDB | 0.00029250767 |
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