| 1,313 |
X-Engine: An Optimized Storage Engine for Large-scale E-commerce Transaction Processing |
2019 |
SIGMOD |
0.00011060108 |
| 1,422 |
The Log-Structured Merge-Bush & the Wacky Continuum |
2019 |
SIGMOD |
0.00010725538 |
| 1,889 |
Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn |
2019 |
CIDR |
9.4273689e-05 |
| 1,980 |
Chucky: A Succinct Cuckoo Filter for LSM-Tree |
2021 |
SIGMOD |
9.2595896e-05 |
| 2,664 |
Rosetta: A Robust Space-Time Optimized Range Filter for Key-Value Stores |
2020 |
SIGMOD |
8.1569551e-05 |
| 2,770 |
Constructing and Analyzing the LSM Compaction Design Space |
2021 |
VLDB |
8.037607e-05 |
| 2,788 |
Lethe: A Tunable Delete-Aware LSM Engine |
2020 |
SIGMOD |
8.0133966e-05 |
| 2,868 |
Spooky: Granulating LSM-Tree Compactions Correctly |
2022 |
VLDB |
7.9241972e-05 |
| 3,486 |
HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements |
2022 |
SIGMOD |
7.2636102e-05 |
| 3,525 |
Key-Value Storage Engines |
2020 |
SIGMOD |
7.2327042e-05 |
| 3,641 |
Nova-LSM: A Distributed, Component-based LSM-tree Key-value Store |
2021 |
SIGMOD |
7.1439198e-05 |
| 3,680 |
SplinterDB and Maplets: Improving the Tradeoffs in Key-Value Store Compaction Policy |
2023 |
SIGMOD |
7.1029718e-05 |
| 4,121 |
On Performance Stability in LSM-based Storage Systems |
2020 |
VLDB |
6.7946812e-05 |
| 4,750 |
GRF: A Global Range Filter for LSM-Trees with Shape Encoding |
2024 |
SIGMOD |
6.4354422e-05 |
| 5,018 |
Breaking Down Memory Walls: Adaptive Memory Management in LSM-based Storage Systems |
2021 |
VLDB |
6.3121723e-05 |
| 5,046 |
Dissecting, Designing, and Optimizing LSM-based Data Stores |
2022 |
SIGMOD |
6.3000825e-05 |
| 5,081 |
InfiniFilter: Expanding Filters to Infinity and Beyond |
2023 |
SIGMOD |
6.2854372e-05 |
| 5,248 |
Endure: A Robust Tuning Paradigm for LSM Trees Under Workload Uncertainty |
2022 |
VLDB |
6.211056e-05 |
| 5,819 |
Spatial Independent Range Sampling |
2021 |
SIGMOD |
5.9832748e-05 |
| 6,025 |
Near-Data Processing in Database Systems on Native Computational Storage under HTAP Workloads |
2022 |
VLDB |
5.9119514e-05 |
| 6,080 |
From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems |
2019 |
SIGMOD |
5.8924903e-05 |
| 6,120 |
LSMGraph: A High-Performance Dynamic Graph Storage System with Multi-Level CSR |
2024 |
SIGMOD |
5.880693e-05 |
| 6,124 |
Learning to Optimize LSM-trees: Towards A Reinforcement Learning based Key-Value Store for Dynamic Workloads |
2023 |
SIGMOD |
5.8788211e-05 |
| 6,192 |
Prefix Filter: Practically and Theoretically Better Than Bloom |
2022 |
VLDB |
5.8555676e-05 |
| 6,238 |
Toward a Better Understanding and Evaluation of Tree Structures on Flash SSDs |
2021 |
VLDB |
5.8385618e-05 |
| 6,500 |
Revisiting the Design of LSM-tree Based OLTP Storage Engine with Persistent Memory |
2021 |
VLDB |
5.7648519e-05 |
| 6,635 |
LSM-Trees and B-Trees: The Best of Both Worlds |
2019 |
SIGMOD |
5.7263609e-05 |
| 7,241 |
CaaS-LSM: Compaction-as-a-Service for LSM-based Key-Value Stores in Storage Disaggregated Infrastructure |
2024 |
SIGMOD |
5.5777445e-05 |
| 7,349 |
TimeUnion: An Efficient Architecture with Unified Data Model for Timeseries Management Systems on Hybrid Cloud Storage |
2022 |
SIGMOD |
5.545453e-05 |
| 7,531 |
Time Series Representation for Visualization in Apache IoTDB |
2024 |
SIGMOD |
5.5008425e-05 |
| 7,594 |
Efficient Data Ingestion and Query Processing for LSM-Based Storage Systems |
2019 |
VLDB |
5.4879453e-05 |
| 7,905 |
CAMAL: Optimizing LSM-trees via Active Learning |
2024 |
SIGMOD |
5.4291824e-05 |
| 7,940 |
Aleph Filter: To Infinity in Constant Time |
2024 |
VLDB |
5.4219572e-05 |
| 8,221 |
ArceKV: Towards Workload-driven LSM-compactions for Key-Value Store Under Dynamic Workloads |
2026 |
VLDB |
5.3759492e-05 |
| 8,329 |
How to Grow an LSM-tree? Towards Bridging the Gap Between Theory and Practice |
2025 |
SIGMOD |
5.3536854e-05 |
| 8,530 |
SA-LSM: Optimize Data Layout for LSM-tree Based Storage using Survival Analysis |
2022 |
VLDB |
5.3222993e-05 |
| 8,620 |
Limousine: Blending Learned and Classical Indexes to Self-Design Larger-than-Memory Cloud Storage Engines |
2024 |
SIGMOD |
5.301557e-05 |
| 8,640 |
Mnemosyne: Dynamic Workload-Aware BF Tuning via Accurate Statistics in LSM trees |
2025 |
SIGMOD |
5.2972383e-05 |
| 8,753 |
A New Paradigm in Tuning Learned Indexes: A Reinforcement Learning Enhanced Approach |
2025 |
SIGMOD |
5.2846898e-05 |
| 8,944 |
Practical Dynamic Extension for Sampling Indexes |
2023 |
SIGMOD |
5.2542285e-05 |
| 8,953 |
FishStore: Faster Ingestion with Subset Hashing |
2019 |
SIGMOD |
5.2515834e-05 |
| 9,003 |
Entropy-Learned Hashing: Constant Time Hashing with Controllable Uniformity |
2022 |
SIGMOD |
5.2392472e-05 |
| 9,056 |
Aster: Enhancing LSM-structures for Scalable Graph Database |
2025 |
SIGMOD |
5.2295363e-05 |
| 9,057 |
BACH: Bridging Adjacency List and CSR Format using LSM-Trees for HGTAP Workloads |
2025 |
VLDB |
5.2295363e-05 |
| 9,081 |
MirrorKV: An Efficient Key-Value Store on Hybrid Cloud Storage with Balanced Performance of Compaction and Querying |
2023 |
SIGMOD |
5.2283159e-05 |
| 9,130 |
Rethinking The Compaction Policies in LSM-trees |
2025 |
SIGMOD |
5.2233025e-05 |
| 9,181 |
Structural Designs Meet Optimality: Exploring Optimized LSM-tree Structures in A Colossal Configuration Space |
2024 |
SIGMOD |
5.2118872e-05 |
| 9,464 |
DFlush: DPU-Offloaded Flush for Disaggregated LSM-based Key-Value Stores |
2025 |
SIGMOD |
5.1727546e-05 |
| 9,646 |
Are Joins over LSM-trees Ready? Take RocksDB as an Example |
2025 |
VLDB |
5.1453267e-05 |
| 9,662 |
The End of Moore’s Law and the Rise of The Data Processor |
2021 |
VLDB |
5.1453267e-05 |