| 1,313 |
X-Engine: An Optimized Storage Engine for Large-scale E-commerce Transaction Processing |
2019 |
SIGMOD |
0.00011055196 |
| 1,422 |
The Log-Structured Merge-Bush & the Wacky Continuum |
2019 |
SIGMOD |
0.00010720711 |
| 1,891 |
Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn |
2019 |
CIDR |
9.4233024e-05 |
| 1,982 |
Chucky: A Succinct Cuckoo Filter for LSM-Tree |
2021 |
SIGMOD |
9.2570284e-05 |
| 2,664 |
Rosetta: A Robust Space-Time Optimized Range Filter for Key-Value Stores |
2020 |
SIGMOD |
8.1532061e-05 |
| 2,771 |
Constructing and Analyzing the LSM Compaction Design Space |
2021 |
VLDB |
8.0338932e-05 |
| 2,788 |
Lethe: A Tunable Delete-Aware LSM Engine |
2020 |
SIGMOD |
8.0114055e-05 |
| 2,868 |
Spooky: Granulating LSM-Tree Compactions Correctly |
2022 |
VLDB |
7.9205462e-05 |
| 3,487 |
HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements |
2022 |
SIGMOD |
7.2603973e-05 |
| 3,525 |
Key-Value Storage Engines |
2020 |
SIGMOD |
7.2293566e-05 |
| 3,643 |
Nova-LSM: A Distributed, Component-based LSM-tree Key-value Store |
2021 |
SIGMOD |
7.1406131e-05 |
| 3,683 |
SplinterDB and Maplets: Improving the Tradeoffs in Key-Value Store Compaction Policy |
2023 |
SIGMOD |
7.0996633e-05 |
| 4,121 |
On Performance Stability in LSM-based Storage Systems |
2020 |
VLDB |
6.7915554e-05 |
| 4,753 |
GRF: A Global Range Filter for LSM-Trees with Shape Encoding |
2024 |
SIGMOD |
6.4334982e-05 |
| 5,022 |
Breaking Down Memory Walls: Adaptive Memory Management in LSM-based Storage Systems |
2021 |
VLDB |
6.309271e-05 |
| 5,041 |
Dissecting, Designing, and Optimizing LSM-based Data Stores |
2022 |
SIGMOD |
6.2998284e-05 |
| 5,084 |
InfiniFilter: Expanding Filters to Infinity and Beyond |
2023 |
SIGMOD |
6.2824822e-05 |
| 5,250 |
Endure: A Robust Tuning Paradigm for LSM Trees Under Workload Uncertainty |
2022 |
VLDB |
6.2092552e-05 |
| 5,821 |
Spatial Independent Range Sampling |
2021 |
SIGMOD |
5.9804424e-05 |
| 6,026 |
Near-Data Processing in Database Systems on Native Computational Storage under HTAP Workloads |
2022 |
VLDB |
5.9091528e-05 |
| 6,081 |
From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems |
2019 |
SIGMOD |
5.8897947e-05 |
| 6,121 |
LSMGraph: A High-Performance Dynamic Graph Storage System with Multi-Level CSR |
2024 |
SIGMOD |
5.8779092e-05 |
| 6,123 |
Learning to Optimize LSM-trees: Towards A Reinforcement Learning based Key-Value Store for Dynamic Workloads |
2023 |
SIGMOD |
5.8771312e-05 |
| 6,195 |
Prefix Filter: Practically and Theoretically Better Than Bloom |
2022 |
VLDB |
5.8528165e-05 |
| 6,242 |
Toward a Better Understanding and Evaluation of Tree Structures on Flash SSDs |
2021 |
VLDB |
5.8358009e-05 |
| 6,499 |
Revisiting the Design of LSM-tree Based OLTP Storage Engine with Persistent Memory |
2021 |
VLDB |
5.7629005e-05 |
| 6,639 |
LSM-Trees and B-Trees: The Best of Both Worlds |
2019 |
SIGMOD |
5.7236527e-05 |
| 7,239 |
CaaS-LSM: Compaction-as-a-Service for LSM-based Key-Value Stores in Storage Disaggregated Infrastructure |
2024 |
SIGMOD |
5.5761767e-05 |
| 7,352 |
TimeUnion: An Efficient Architecture with Unified Data Model for Timeseries Management Systems on Hybrid Cloud Storage |
2022 |
SIGMOD |
5.5428278e-05 |
| 7,537 |
Time Series Representation for Visualization in Apache IoTDB |
2024 |
SIGMOD |
5.4982385e-05 |
| 7,593 |
Efficient Data Ingestion and Query Processing for LSM-Based Storage Systems |
2019 |
VLDB |
5.4870235e-05 |
| 7,909 |
CAMAL: Optimizing LSM-trees via Active Learning |
2024 |
SIGMOD |
5.4266123e-05 |
| 7,944 |
Aleph Filter: To Infinity in Constant Time |
2024 |
VLDB |
5.4193905e-05 |
| 8,228 |
ArceKV: Towards Workload-driven LSM-compactions for Key-Value Store Under Dynamic Workloads |
2026 |
VLDB |
5.3734043e-05 |
| 8,326 |
How to Grow an LSM-tree? Towards Bridging the Gap Between Theory and Practice |
2025 |
SIGMOD |
5.3522236e-05 |
| 8,538 |
SA-LSM: Optimize Data Layout for LSM-tree Based Storage using Survival Analysis |
2022 |
VLDB |
5.3197798e-05 |
| 8,619 |
Limousine: Blending Learned and Classical Indexes to Self-Design Larger-than-Memory Cloud Storage Engines |
2024 |
SIGMOD |
5.3001199e-05 |
| 8,647 |
Mnemosyne: Dynamic Workload-Aware BF Tuning via Accurate Statistics in LSM trees |
2025 |
SIGMOD |
5.2947307e-05 |
| 8,761 |
A New Paradigm in Tuning Learned Indexes: A Reinforcement Learning Enhanced Approach |
2025 |
SIGMOD |
5.2821881e-05 |
| 8,953 |
Practical Dynamic Extension for Sampling Indexes |
2023 |
SIGMOD |
5.2517412e-05 |
| 8,961 |
FishStore: Faster Ingestion with Subset Hashing |
2019 |
SIGMOD |
5.2490978e-05 |
| 9,013 |
Entropy-Learned Hashing: Constant Time Hashing with Controllable Uniformity |
2022 |
SIGMOD |
5.236767e-05 |
| 9,064 |
Aster: Enhancing LSM-structures for Scalable Graph Database |
2025 |
SIGMOD |
5.2270607e-05 |
| 9,065 |
BACH: Bridging Adjacency List and CSR Format using LSM-Trees for HGTAP Workloads |
2025 |
VLDB |
5.2270607e-05 |
| 9,091 |
MirrorKV: An Efficient Key-Value Store on Hybrid Cloud Storage with Balanced Performance of Compaction and Querying |
2023 |
SIGMOD |
5.2258409e-05 |
| 9,140 |
Rethinking The Compaction Policies in LSM-trees |
2025 |
SIGMOD |
5.2208299e-05 |
| 9,191 |
Structural Designs Meet Optimality: Exploring Optimized LSM-tree Structures in A Colossal Configuration Space |
2024 |
SIGMOD |
5.20942e-05 |
| 9,475 |
DFlush: DPU-Offloaded Flush for Disaggregated LSM-based Key-Value Stores |
2025 |
SIGMOD |
5.1703059e-05 |
| 9,654 |
Are Joins over LSM-trees Ready? Take RocksDB as an Example |
2025 |
VLDB |
5.142891e-05 |
| 9,669 |
The End of Moore’s Law and the Rise of The Data Processor |
2021 |
VLDB |
5.142891e-05 |