| 1,391 |
X-Engine: An Optimized Storage Engine for Large-scale E-commerce Transaction Processing |
2019 |
SIGMOD |
0.00011022485 |
| 1,490 |
The Log-Structured Merge-Bush & the Wacky Continuum |
2019 |
SIGMOD |
0.00010670432 |
| 1,925 |
Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn |
2019 |
CIDR |
9.5601154e-05 |
| 2,033 |
Chucky: A Succinct Cuckoo Filter for LSM-Tree |
2021 |
SIGMOD |
9.3611235e-05 |
| 2,721 |
Lethe: A Tunable Delete-Aware LSM Engine |
2020 |
SIGMOD |
8.2688149e-05 |
| 2,798 |
Rosetta: A Robust Space-Time Optimized Range Filter for Key-Value Stores |
2020 |
SIGMOD |
8.1764761e-05 |
| 2,981 |
Constructing and Analyzing the LSM Compaction Design Space |
2021 |
VLDB |
7.9488888e-05 |
| 3,176 |
Spooky: Granulating LSM-Tree Compactions Correctly |
2022 |
VLDB |
7.7392804e-05 |
| 3,539 |
HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements |
2022 |
SIGMOD |
7.3903311e-05 |
| 3,924 |
Nova-LSM: A Distributed, Component-based LSM-tree Key-value Store |
2021 |
SIGMOD |
7.0818503e-05 |
| 4,191 |
SplinterDB and Maplets: Improving the Tradeoffs in Key-Value Store Compaction Policy |
2023 |
SIGMOD |
6.9073432e-05 |
| 4,232 |
On Performance Stability in LSM-based Storage Systems |
2020 |
VLDB |
6.8805039e-05 |
| 4,931 |
Key-Value Storage Engines |
2020 |
SIGMOD |
6.5035688e-05 |
| 5,179 |
Dissecting, Designing, and Optimizing LSM-based Data Stores |
2022 |
SIGMOD |
6.3975112e-05 |
| 5,184 |
Breaking Down Memory Walls: Adaptive Memory Management in LSM-based Storage Systems |
2021 |
VLDB |
6.3945246e-05 |
| 5,199 |
GRF: A Global Range Filter for LSM-Trees with Shape Encoding |
2024 |
SIGMOD |
6.3907666e-05 |
| 5,302 |
InfiniFilter: Expanding Filters to Infinity and Beyond |
2023 |
SIGMOD |
6.3443167e-05 |
| 5,713 |
Endure: A Robust Tuning Paradigm for LSM Trees Under Workload Uncertainty |
2022 |
VLDB |
6.1790178e-05 |
| 5,909 |
From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems |
2019 |
SIGMOD |
6.106668e-05 |
| 6,086 |
Toward a Better Understanding and Evaluation of Tree Structures on Flash SSDs |
2021 |
VLDB |
6.0439399e-05 |
| 6,231 |
Spatial Independent Range Sampling |
2021 |
SIGMOD |
6.0077421e-05 |
| 6,483 |
Prefix Filter: Practically and Theoretically Better Than Bloom |
2022 |
VLDB |
5.9241139e-05 |
| 6,574 |
Revisiting the Design of LSM-tree Based OLTP Storage Engine with Persistent Memory |
2021 |
VLDB |
5.8920394e-05 |
| 7,082 |
TimeUnion: An Efficient Architecture with Unified Data Model for Timeseries Management Systems on Hybrid Cloud Storage |
2022 |
SIGMOD |
5.7605915e-05 |
| 7,152 |
LSM-Trees and B-Trees: The Best of Both Worlds |
2019 |
SIGMOD |
5.7461385e-05 |
| 7,166 |
Learning to Optimize LSM-trees: Towards A Reinforcement Learning based Key-Value Store for Dynamic Workloads |
2023 |
SIGMOD |
5.7412668e-05 |
| 7,319 |
LSMGraph: A High-Performance Dynamic Graph Storage System with Multi-Level CSR |
2024 |
SIGMOD |
5.7020927e-05 |
| 7,321 |
Near-Data Processing in Database Systems on Native Computational Storage under HTAP Workloads |
2022 |
VLDB |
5.7016585e-05 |
| 7,334 |
Efficient Data Ingestion and Query Processing for LSM-Based Storage Systems |
2019 |
VLDB |
5.698753e-05 |
| 7,565 |
CaaS-LSM: Compaction-as-a-Service for LSM-based Key-Value Stores in Storage Disaggregated Infrastructure |
2024 |
SIGMOD |
5.652556e-05 |
| 7,644 |
CAMAL: Optimizing LSM-trees via Active Learning |
2024 |
SIGMOD |
5.6327117e-05 |
| 8,050 |
How to Grow an LSM-tree? Towards Bridging the Gap Between Theory and Practice |
2025 |
SIGMOD |
5.557279e-05 |
| 8,255 |
SA-LSM: Optimize Data Layout for LSM-tree Based Storage using Survival Analysis |
2022 |
VLDB |
5.521639e-05 |
| 8,303 |
Time Series Representation for Visualization in Apache IoTDB |
2024 |
SIGMOD |
5.5112019e-05 |
| 8,343 |
Limousine: Blending Learned and Classical Indexes to Self-Design Larger-than-Memory Cloud Storage Engines |
2024 |
SIGMOD |
5.5045113e-05 |
| 8,614 |
Aleph Filter: To Infinity in Constant Time |
2024 |
VLDB |
5.4598872e-05 |
| 8,683 |
FishStore: Faster Ingestion with Subset Hashing |
2019 |
SIGMOD |
5.4524014e-05 |
| 8,692 |
ArceKV: Towards Workload-driven LSM-compactions for Key-Value Store Under Dynamic Workloads |
2026 |
VLDB |
5.4483927e-05 |
| 8,754 |
Entropy-Learned Hashing: Constant Time Hashing with Controllable Uniformity |
2022 |
SIGMOD |
5.4354614e-05 |
| 8,788 |
MirrorKV: An Efficient Key-Value Store on Hybrid Cloud Storage with Balanced Performance of Compaction and Querying |
2023 |
SIGMOD |
5.4311509e-05 |
| 8,895 |
Structural Designs Meet Optimality: Exploring Optimized LSM-tree Structures in A Colossal Configuration Space |
2024 |
SIGMOD |
5.4131079e-05 |
| 9,322 |
Rethinking The Compaction Policies in LSM-trees |
2025 |
SIGMOD |
5.3458264e-05 |
| 9,327 |
Are Joins over LSM-trees Ready? Take RocksDB as an Example |
2025 |
VLDB |
5.3449422e-05 |
| 9,367 |
FluidKV: Seamlessly Bridging the Gap between Indexing Performance and Memory-Footprint on Ultra-Fast Storage |
2024 |
VLDB |
5.339939e-05 |
| 9,387 |
Disco: A Compact Index for LSM-trees |
2025 |
SIGMOD |
5.3347424e-05 |
| 9,458 |
Mnemosyne: Dynamic Workload-Aware BF Tuning via Accurate Statistics in LSM trees |
2025 |
SIGMOD |
5.3285846e-05 |
| 9,606 |
A New Paradigm in Tuning Learned Indexes: A Reinforcement Learning Enhanced Approach |
2025 |
SIGMOD |
5.3077157e-05 |
| 9,751 |
Practical Dynamic Extension for Sampling Indexes |
2023 |
SIGMOD |
5.278119e-05 |
| 9,785 |
Optimizing Time Series Queries with Versions |
2024 |
SIGMOD |
5.2719963e-05 |
| 9,818 |
NEXT: A New Secondary Index Framework for LSM-based Data Storage |
2025 |
SIGMOD |
5.2648912e-05 |