| 2,004 |
X-Engine: An Optimized Storage Engine for Large-scale E-commerce Transaction Processing |
2019 |
SIGMOD |
9.811707e-05 |
| 2,109 |
The Log-Structured Merge-Bush & the Wacky Continuum |
2019 |
SIGMOD |
9.5318694e-05 |
| 2,606 |
Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn |
2019 |
CIDR |
8.4645832e-05 |
| 2,798 |
Chucky: A Succinct Cuckoo Filter for LSM-Tree |
2021 |
SIGMOD |
8.1080111e-05 |
| 3,386 |
Lethe: A Tunable Delete-Aware LSM Engine |
2020 |
SIGMOD |
7.1577103e-05 |
| 3,544 |
Rosetta: A Robust Space-Time Optimized Range Filter for Key-Value Stores |
2020 |
SIGMOD |
6.9898874e-05 |
| 3,793 |
Constructing and Analyzing the LSM Compaction Design Space |
2021 |
VLDB |
6.7617833e-05 |
| 3,965 |
Spooky: Granulating LSM-Tree Compactions Correctly |
2022 |
VLDB |
6.5820028e-05 |
| 4,399 |
HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements |
2022 |
SIGMOD |
6.2225151e-05 |
| 4,662 |
Nova-LSM: A Distributed, Component-based LSM-tree Key-value Store |
2021 |
SIGMOD |
6.013415e-05 |
| 4,914 |
On Performance Stability in LSM-based Storage Systems |
2020 |
VLDB |
5.8315684e-05 |
| 4,945 |
SplinterDB and Maplets: Improving the Tradeoffs in Key-Value Store Compaction Policy |
2023 |
SIGMOD |
5.8157107e-05 |
| 5,308 |
Key-Value Storage Engines |
2020 |
SIGMOD |
5.576303e-05 |
| 5,739 |
InfiniFilter: Expanding Filters to Infinity and Beyond |
2023 |
SIGMOD |
5.3471718e-05 |
| 5,791 |
Dissecting, Designing, and Optimizing LSM-based Data Stores |
2022 |
SIGMOD |
5.3268999e-05 |
| 5,863 |
GRF: A Global Range Filter for LSM-Trees with Shape Encoding |
2024 |
SIGMOD |
5.2979639e-05 |
| 5,918 |
Breaking Down Memory Walls: Adaptive Memory Management in LSM-based Storage Systems |
2021 |
VLDB |
5.2737135e-05 |
| 5,953 |
Spatial Independent Range Sampling |
2021 |
SIGMOD |
5.2589924e-05 |
| 6,398 |
Endure: A Robust Tuning Paradigm for LSM Trees Under Workload Uncertainty |
2022 |
VLDB |
5.0819209e-05 |
| 6,456 |
From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems |
2019 |
SIGMOD |
5.0564619e-05 |
| 6,460 |
Toward a Better Understanding and Evaluation of Tree Structures on Flash SSDs |
2021 |
VLDB |
5.0554178e-05 |
| 6,831 |
Prefix Filter: Practically and Theoretically Better Than Bloom |
2022 |
VLDB |
4.9130458e-05 |
| 7,106 |
Revisiting the Design of LSM-tree Based OLTP Storage Engine with Persistent Memory |
2021 |
VLDB |
4.8300429e-05 |
| 7,168 |
TimeUnion: An Efficient Architecture with Unified Data Model for Timeseries Management Systems on Hybrid Cloud Storage |
2022 |
SIGMOD |
4.8121704e-05 |
| 7,343 |
LSM-Trees and B-Trees: The Best of Both Worlds |
2019 |
SIGMOD |
4.7568442e-05 |
| 7,620 |
Learning to Optimize LSM-trees: Towards A Reinforcement Learning based Key-Value Store for Dynamic Workloads |
2023 |
SIGMOD |
4.693568e-05 |
| 7,688 |
Near-Data Processing in Database Systems on Native Computational Storage under HTAP Workloads |
2022 |
VLDB |
4.6772837e-05 |
| 7,694 |
LSMGraph: A High-Performance Dynamic Graph Storage System with Multi-Level CSR |
2024 |
SIGMOD |
4.6757592e-05 |
| 7,743 |
Efficient Data Ingestion and Query Processing for LSM-Based Storage Systems |
2019 |
VLDB |
4.6626575e-05 |
| 7,808 |
CaaS-LSM: Compaction-as-a-Service for LSM-based Key-Value Stores in Storage Disaggregated Infrastructure |
2024 |
SIGMOD |
4.6455813e-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 |
| 8,434 |
Time Series Representation for Visualization in Apache IoTDB |
2024 |
SIGMOD |
4.5141748e-05 |
| 8,491 |
SA-LSM: Optimize Data Layout for LSM-tree Based Storage using Survival Analysis |
2022 |
VLDB |
4.4993073e-05 |
| 8,525 |
Aleph Filter: To Infinity in Constant Time |
2024 |
VLDB |
4.4937074e-05 |
| 8,627 |
Limousine: Blending Learned and Classical Indexes to Self-Design Larger-than-Memory Cloud Storage Engines |
2024 |
SIGMOD |
4.4829101e-05 |
| 8,720 |
Entropy-Learned Hashing: Constant Time Hashing with Controllable Uniformity |
2022 |
SIGMOD |
4.4609699e-05 |
| 8,788 |
FishStore: Faster Ingestion with Subset Hashing |
2019 |
SIGMOD |
4.451039e-05 |
| 8,805 |
ArceKV: Towards Workload-driven LSM-compactions for Key-Value Store Under Dynamic Workloads |
2026 |
VLDB |
4.4466855e-05 |
| 8,876 |
MirrorKV: An Efficient Key-Value Store on Hybrid Cloud Storage with Balanced Performance of Compaction and Querying |
2023 |
SIGMOD |
4.4304279e-05 |
| 9,071 |
Structural Designs Meet Optimality: Exploring Optimized LSM-tree Structures in A Colossal Configuration Space |
2024 |
SIGMOD |
4.4025274e-05 |
| 9,317 |
Are Joins over LSM-trees Ready? Take RocksDB as an Example |
2025 |
VLDB |
4.3556432e-05 |
| 9,362 |
FluidKV: Seamlessly Bridging the Gap between Indexing Performance and Memory-Footprint on Ultra-Fast Storage |
2024 |
VLDB |
4.3503444e-05 |
| 9,386 |
Rethinking The Compaction Policies in LSM-trees |
2025 |
SIGMOD |
4.3455975e-05 |
| 9,465 |
Disco: A Compact Index for LSM-trees |
2025 |
SIGMOD |
4.3350926e-05 |
| 9,529 |
Mnemosyne: Dynamic Workload-Aware BF Tuning via Accurate Statistics in LSM trees |
2025 |
SIGMOD |
4.32934e-05 |
| 9,618 |
A New Paradigm in Tuning Learned Indexes: A Reinforcement Learning Enhanced Approach |
2025 |
SIGMOD |
4.3173366e-05 |
| 9,758 |
Practical Dynamic Extension for Sampling Indexes |
2023 |
SIGMOD |
4.2879116e-05 |
| 9,792 |
Optimizing Time Series Queries with Versions |
2024 |
SIGMOD |
4.2818172e-05 |
| 9,824 |
NEXT: A New Secondary Index Framework for LSM-based Data Storage |
2025 |
SIGMOD |
4.2751057e-05 |