Beyond Compression: A Comprehensive Evaluation of Lossless Floating-Point Compression
Summary: Comprehensive empirical evaluation of lossless floating-point compressors for columnar engines, measuring compression ratio, in-situ DB query performance, and ML queries (distance, k-NN/RAG); implemented in Rust and released as a library. Finds clear trade-offs: no single method dominates both space and query speed—some compressors yield higher compression but slower DB/ML query performance. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Kaisei Hishida
- 2. Chunwei Liu
- 3. John Paparrizos
- 4. Aaron J. Elmore
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,746 | Time-Series Clustering: A Comprehensive Study of Data Mining, Machine Learning, and Deep Learning Methods | 2025 | VLDB | 4.1905499e-05 |
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