Optimizing Time Series Queries with Versions
Summary: Time-series/IoT DBs are inherently multi-versioned under LSM storage; the paper introduces a version-operator algebra to formalize merge semantics and optimize queries over versioned blocks. Key idea: version reducibility enables consistent plans that defer costly merges, with SQL translation for relational integration. (summarized by gpt-5.4-mini on May 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Rui Kang (Tsinghua University)
- 2. Shaoxu Song (Tsinghua University)
BibTeX Citation
@inproceedings{kang_sigmod24,
title = {{Optimizing Time Series Queries with Versions}},
author = {Kang, Rui and Song, Shaoxu},
series = {{SIGMOD} '24},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3654962},
url = {https://dl.acm.org/doi/10.1145/3654962},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,360 | STsCache: An Efficient Semantic Caching Scheme for Time-series Data Workloads Based on Hybrid Storage | 2025 | VLDB | 4.9605343e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 19 of 19 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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