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Swan: Hybrid MVCC Management for Efficient Transaction Processing in LSM-Tree-Based Key-Value Stores
Summary: Swan hybridizes in-memory and out-of-memory MVCC, pairing fast visibility checks with low commit latency and memory use for large write transactions. Transaction-aware separation, an uncommitted-data stash, and concurrent memtable flushing adapt MVCC to LSM stores.
(summarized by gpt-5.6-luna on Aug 17 2026)
Paper ID
h1f4737335cd60d9e
Venue
VLDB
Year
2026
Pagerank
4.9793485e-05
Overall Rank
10,763 | 27.64%
DOI
10.14778/3819518.3819528
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
1.
Yang Guo
(Chinese University of Hong Kong)
2.
Jin Xue
(Chinese University of Hong Kong)
3.
Zili Shao
(Chinese University of Hong Kong)
BibTeX Citation
Copy BibTeX
@article{guo_vldb26,
title = {{Swan: Hybrid MVCC Management for Efficient Transaction Processing in LSM-Tree-Based Key-Value Stores}},
author = {Guo, Yang and Xue, Jin and Shao, Zili},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {9},
pages = {1977--1990},
doi = {10.14778/3819518.3819528},
url = {https://doi.org/10.14778/3819518.3819528},
year = {2026}
}
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Citing Paper
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Venue
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Outgoing Citations (Sorted by Pagerank)
Showing 31 of 31 cited papers.
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