High-Performance Query Processing with NVMe Arrays: Spilling without Killing Performance
Summary: Adaptive materialization turns in-memory hash operators into spill-friendly OOM operators without sacrificing in-memory speed. Self-regulating compression optimizes spilling throughput on NVMe arrays, enabling Spilly to match in-memory performance while handling large out-of-memory workloads. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Maximilian Kuschewski (Technical University of Munich)
- 2. Jana Giceva (Technical University of Munich)
- 3. Thomas Neumann (Technical University of Munich)
- 4. Viktor Leis (Technical University of Munich)
BibTeX Citation
@inproceedings{kuschewski_sigmod24,
title = {{High-Performance Query Processing with NVMe Arrays: Spilling without Killing Performance}},
author = {Kuschewski, Maximilian and Giceva, Jana and Neumann, Thomas and Leis, Viktor},
series = {{SIGMOD} '24},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3698813},
url = {https://dl.acm.org/doi/10.1145/3698813},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
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| 9,243 | CloudGlide: Deconstructing the Landscape of Cloud-Based Analytics | 2025 | VLDB | 5.1864799e-05 |
| 9,832 | Declarative Memory Services | 2026 | CIDR | 5.1064323e-05 |
| 10,796 | How to Write to SSDs | 2026 | VLDB | 4.9605343e-05 |
| 10,904 | BtrLog: Low-Latency Logging for Cloud Database Systems | 2026 | VLDB | 4.9605343e-05 |
| 11,107 | Future-Proof Data Systems | 2026 | VLDB | 4.9605343e-05 |
| 11,404 | Towards Designing Future-Proof Data Processing Systems | 2025 | VLDB | 4.9605343e-05 |
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