OptiQL: Robust Optimistic Locking for Memory-Optimized Indexes
Summary: OptiQL extends the MCS lock with optimistic reads for memory-optimized B+-trees, delivering contention robustness while preserving a compact 8-byte lock and fairness. Evaluated on a 40-core dual-socket server, OptiQL matches read performance of existing optimistic locks and prevents collapse under high contention. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ge Shi (Simon Fraser University)
- 2. Ziyi Yan (Simon Fraser University)
- 3. Tianzheng Wang (Simon Fraser University)
BibTeX Citation
@inproceedings{shi_sigmod23,
title = {{OptiQL: Robust Optimistic Locking for Memory-Optimized Indexes}},
author = {Shi, Ge and Yan, Ziyi and Wang, Tianzheng},
series = {{SIGMOD} '23},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3617336},
url = {https://dl.acm.org/doi/10.1145/3617336},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,852 | DEX: Scalable Range Indexing on Disaggregated Memory | 2024 | VLDB | 6.0658952e-05 |
| 9,547 | Tabular: Efficiently Building Efficient Indexes | 2025 | VLDB | 5.2528121e-05 |
| 10,482 | Predictive Translation: High-Performance Buffer Management Without the Trade-Offs | 2026 | SIGMOD | 5.093636e-05 |
| 10,568 | Operation-Aware Hybrid Locking for Modern In-Memory Indexes | 2026 | VLDB | 5.093636e-05 |
| 10,829 | FB+-tree: A Memory-Optimized B+-tree with Latch-Free Update | 2025 | VLDB | 5.093636e-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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