Bullion: A Column Store for Machine Learning
Summary: Bullion is a columnar store tailored for ML: modular cascading encodings, in‑storage feature quantization, optimized long-sequence sparse‑feature encodings, and quality‑aware sequential reads for wide-table/multimodal training. Yields lower I/O for deletion compliance, substantial storage savings on sparse features, and faster metadata parsing than existing column stores. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Gang Liao (University of Maryland)
- 2. Ye Liu (ByteDance)
- 3. Jianjun Chen (ByteDance)
- 4. Daniel J. Abadi (University of Maryland)
BibTeX Citation
@inproceedings{liao_cidr25,
address = {Amsterdam, Netherlands},
series = {{CIDR} '25},
title = {{Bullion: A Column Store for Machine Learning}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Liao, Gang and Liu, Ye and Chen, Jianjun and Abadi, Daniel J.},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,559 | F3: The Open-Source Data File Format for the Future | 2026 | SIGMOD | 5.3141911e-05 |
| 8,577 | The FastLanes File Format | 2025 | VLDB | 5.3107348e-05 |
| 8,646 | Magnus: A Holistic Approach to Data Management for Large-Scale Machine Learning Workloads | 2025 | VLDB | 5.2953847e-05 |
| 10,027 | Towards Functional Decomposition of Storage Formats | 2025 | CIDR | 5.0917543e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 27 of 27 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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