| 1,324 |
X-Engine: An Optimized Storage Engine for Large-scale E-commerce Transaction Processing |
2019 |
SIGMOD |
0.00011019001 |
| 1,429 |
The Log-Structured Merge-Bush & the Wacky Continuum |
2019 |
SIGMOD |
0.00010685393 |
| 1,900 |
Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn |
2019 |
CIDR |
9.3926585e-05 |
| 1,991 |
Chucky: A Succinct Cuckoo Filter for LSM-Tree |
2021 |
SIGMOD |
9.2264312e-05 |
| 2,667 |
Rosetta: A Robust Space-Time Optimized Range Filter for Key-Value Stores |
2020 |
SIGMOD |
8.1324472e-05 |
| 2,780 |
Constructing and Analyzing the LSM Compaction Design Space |
2021 |
VLDB |
8.0073289e-05 |
| 2,796 |
Lethe: A Tunable Delete-Aware LSM Engine |
2020 |
SIGMOD |
7.9849253e-05 |
| 2,882 |
Spooky: Granulating LSM-Tree Compactions Correctly |
2022 |
VLDB |
7.894356e-05 |
| 3,486 |
HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements |
2022 |
SIGMOD |
7.2428834e-05 |
| 3,532 |
Key-Value Storage Engines |
2020 |
SIGMOD |
7.2054521e-05 |
| 3,650 |
Nova-LSM: A Distributed, Component-based LSM-tree Key-value Store |
2021 |
SIGMOD |
7.1170026e-05 |
| 3,692 |
SplinterDB and Maplets: Improving the Tradeoffs in Key-Value Store Compaction Policy |
2023 |
SIGMOD |
7.0761873e-05 |
| 4,141 |
On Performance Stability in LSM-based Storage Systems |
2020 |
VLDB |
6.7690985e-05 |
| 4,771 |
GRF: A Global Range Filter for LSM-Trees with Shape Encoding |
2024 |
SIGMOD |
6.412225e-05 |
| 5,046 |
Breaking Down Memory Walls: Adaptive Memory Management in LSM-based Storage Systems |
2021 |
VLDB |
6.2884087e-05 |
| 5,065 |
Dissecting, Designing, and Optimizing LSM-based Data Stores |
2022 |
SIGMOD |
6.2789973e-05 |
| 5,082 |
InfiniFilter: Expanding Filters to Infinity and Beyond |
2023 |
SIGMOD |
6.2679091e-05 |
| 5,272 |
Endure: A Robust Tuning Paradigm for LSM Trees Under Workload Uncertainty |
2022 |
VLDB |
6.1887235e-05 |
| 5,835 |
Spatial Independent Range Sampling |
2021 |
SIGMOD |
5.9606673e-05 |
| 6,031 |
Near-Data Processing in Database Systems on Native Computational Storage under HTAP Workloads |
2022 |
VLDB |
5.8909681e-05 |
| 6,095 |
From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems |
2019 |
SIGMOD |
5.8706416e-05 |
| 6,135 |
LSMGraph: A High-Performance Dynamic Graph Storage System with Multi-Level CSR |
2024 |
SIGMOD |
5.8584732e-05 |
| 6,137 |
Learning to Optimize LSM-trees: Towards A Reinforcement Learning based Key-Value Store for Dynamic Workloads |
2023 |
SIGMOD |
5.8576977e-05 |
| 6,205 |
Prefix Filter: Practically and Theoretically Better Than Bloom |
2022 |
VLDB |
5.8336044e-05 |
| 6,255 |
Toward a Better Understanding and Evaluation of Tree Structures on Flash SSDs |
2021 |
VLDB |
5.8165041e-05 |
| 6,513 |
Revisiting the Design of LSM-tree Based OLTP Storage Engine with Persistent Memory |
2021 |
VLDB |
5.7438448e-05 |
| 6,649 |
LSM-Trees and B-Trees: The Best of Both Worlds |
2019 |
SIGMOD |
5.7047276e-05 |
| 7,258 |
CaaS-LSM: Compaction-as-a-Service for LSM-based Key-Value Stores in Storage Disaggregated Infrastructure |
2024 |
SIGMOD |
5.5577384e-05 |
| 7,374 |
TimeUnion: An Efficient Architecture with Unified Data Model for Timeseries Management Systems on Hybrid Cloud Storage |
2022 |
SIGMOD |
5.5244998e-05 |
| 7,554 |
Time Series Representation for Visualization in Apache IoTDB |
2024 |
SIGMOD |
5.4800579e-05 |
| 7,609 |
Efficient Data Ingestion and Query Processing for LSM-Based Storage Systems |
2019 |
VLDB |
5.46888e-05 |
| 7,925 |
CAMAL: Optimizing LSM-trees via Active Learning |
2024 |
SIGMOD |
5.4086685e-05 |
| 7,959 |
Aleph Filter: To Infinity in Constant Time |
2024 |
VLDB |
5.4014706e-05 |
| 8,245 |
ArceKV: Towards Workload-driven LSM-compactions for Key-Value Store Under Dynamic Workloads |
2026 |
VLDB |
5.3556365e-05 |
| 8,342 |
How to Grow an LSM-tree? Towards Bridging the Gap Between Theory and Practice |
2025 |
SIGMOD |
5.3345258e-05 |
| 8,555 |
SA-LSM: Optimize Data Layout for LSM-tree Based Storage using Survival Analysis |
2022 |
VLDB |
5.3021893e-05 |
| 8,638 |
Limousine: Blending Learned and Classical Indexes to Self-Design Larger-than-Memory Cloud Storage Engines |
2024 |
SIGMOD |
5.2825944e-05 |
| 8,666 |
Mnemosyne: Dynamic Workload-Aware BF Tuning via Accurate Statistics in LSM trees |
2025 |
SIGMOD |
5.277223e-05 |
| 8,782 |
A New Paradigm in Tuning Learned Indexes: A Reinforcement Learning Enhanced Approach |
2025 |
SIGMOD |
5.2647219e-05 |
| 8,976 |
Practical Dynamic Extension for Sampling Indexes |
2023 |
SIGMOD |
5.2343756e-05 |
| 8,983 |
FishStore: Faster Ingestion with Subset Hashing |
2019 |
SIGMOD |
5.2317424e-05 |
| 9,034 |
Entropy-Learned Hashing: Constant Time Hashing with Controllable Uniformity |
2022 |
SIGMOD |
5.219451e-05 |
| 9,084 |
Aster: Enhancing LSM-structures for Scalable Graph Database |
2025 |
SIGMOD |
5.2097768e-05 |
| 9,085 |
BACH: Bridging Adjacency List and CSR Format using LSM-Trees for HGTAP Workloads |
2025 |
VLDB |
5.2097768e-05 |
| 9,111 |
MirrorKV: An Efficient Key-Value Store on Hybrid Cloud Storage with Balanced Performance of Compaction and Querying |
2023 |
SIGMOD |
5.208561e-05 |
| 9,162 |
Rethinking The Compaction Policies in LSM-trees |
2025 |
SIGMOD |
5.2035666e-05 |
| 9,215 |
Structural Designs Meet Optimality: Exploring Optimized LSM-tree Structures in A Colossal Configuration Space |
2024 |
SIGMOD |
5.1921944e-05 |
| 9,503 |
DFlush: DPU-Offloaded Flush for Disaggregated LSM-based Key-Value Stores |
2025 |
SIGMOD |
5.1532096e-05 |
| 9,681 |
Are Joins over LSM-trees Ready? Take RocksDB as an Example |
2025 |
VLDB |
5.1258854e-05 |
| 9,698 |
The End of Moore’s Law and the Rise of The Data Processor |
2021 |
VLDB |
5.1258854e-05 |