Mnemosyne: Dynamic Workload-Aware BF Tuning via Accurate Statistics in LSM trees
Summary: Mnemosyne dynamically reallocates Bloom Filters for evolving LSM trees, tuning memory without workload knowledge. It adds Merlin, a sliding-window per-file tracker, and Mnemosyne+ with a refined per-file cost model. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zichen Zhu
- 2. Yanpeng Wei
- 3. Ju Hyoung Mun
- 4. Manos Athanassoulis
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,805 | ArceKV: Towards Workload-driven LSM-compactions for Key-Value Store Under Dynamic Workloads | 2026 | VLDB | 4.4466855e-05 |
| 10,176 | Improving Range Scan Performance in LSM-trees with Group Caching | 2026 | SIGMOD | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 25 of 25 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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| 9,071 | Structural Designs Meet Optimality: Exploring Optimized LSM-tree Structures in A Colossal Configuration Space | 2024 | SIGMOD | 4.4025274e-05 |
| 609 | Monkey: Optimal Navigable Key-Value Store | 2017 | SIGMOD | 0.0001923446 |
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