Structural Designs Meet Optimality: Exploring Optimized LSM-tree Structures in A Colossal Configuration Space
Summary: LSM-tree design space generalized beyond fixed leveled/Tiered patterns: per-level runs, size ratios, and Bloom filters are optimized jointly. Key insight is a large last level for point lookups plus a runs/ratio correlation yielding Moose/Smoose, outperforming RocksDB baselines across mixed workloads. (summarized by gpt-5.4-mini on May 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Junfeng Liu
- 2. Fan Wang
- 3. Dingheng Mo
- 4. Siqiang Luo
Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,762 | Oasis: An Optimal Disjoint Segmented Learned Range Filter | 2024 | VLDB | 5.3377299e-05 |
| 8,009 | CAMAL: Optimizing LSM-trees via Active Learning | 2024 | SIGMOD | 4.6066863e-05 |
| 8,339 | How to Grow an LSM-tree? Towards Bridging the Gap Between Theory and Practice | 2025 | SIGMOD | 4.5434069e-05 |
| 8,805 | ArceKV: Towards Workload-driven LSM-compactions for Key-Value Store Under Dynamic Workloads | 2026 | VLDB | 4.4466855e-05 |
| 9,317 | Are Joins over LSM-trees Ready? Take RocksDB as an Example | 2025 | VLDB | 4.3556432e-05 |
| 9,386 | Rethinking The Compaction Policies in LSM-trees | 2025 | SIGMOD | 4.3455975e-05 |
| 10,176 | Improving Range Scan Performance in LSM-trees with Group Caching | 2026 | SIGMOD | 4.1945683e-05 |
| 10,367 | Aster: Enhancing LSM-structures for Scalable Graph Database | 2025 | SIGMOD | 4.1945683e-05 |
| 10,849 | AXE: A Task Decomposition Approach to Learned LSM Tuning | 2025 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 37 of 37 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,176 | Improving Range Scan Performance in LSM-trees with Group Caching | 2026 | SIGMOD | 4.1945683e-05 |
| 3,793 | Constructing and Analyzing the LSM Compaction Design Space | 2021 | VLDB | 6.7617833e-05 |
| 5,791 | Dissecting, Designing, and Optimizing LSM-based Data Stores | 2022 | SIGMOD | 5.3268999e-05 |
| 7,743 | Efficient Data Ingestion and Query Processing for LSM-Based Storage Systems | 2019 | VLDB | 4.6626575e-05 |
| 9,386 | Rethinking The Compaction Policies in LSM-trees | 2025 | SIGMOD | 4.3455975e-05 |
| 7,218 | Breaking Down Memory Walls in LSM-based Storage Systems | 2020 | SIGMOD | 4.7982543e-05 |
| 2,109 | The Log-Structured Merge-Bush & the Wacky Continuum | 2019 | SIGMOD | 9.5318694e-05 |
| 7,343 | LSM-Trees and B-Trees: The Best of Both Worlds | 2019 | SIGMOD | 4.7568442e-05 |
| 609 | Monkey: Optimal Navigable Key-Value Store | 2017 | SIGMOD | 0.0001923446 |
| 7,620 | Learning to Optimize LSM-trees: Towards A Reinforcement Learning based Key-Value Store for Dynamic Workloads | 2023 | SIGMOD | 4.693568e-05 |