| 2,797 |
Chucky: A Succinct Cuckoo Filter for LSM-Tree |
2021 |
SIGMOD |
8.1116755e-05 |
| 3,363 |
Lethe: A Tunable Delete-Aware LSM Engine |
2020 |
SIGMOD |
7.1680649e-05 |
| 3,545 |
Rosetta: A Robust Space-Time Optimized Range Filter for Key-Value Stores |
2020 |
SIGMOD |
6.9831585e-05 |
| 3,797 |
Constructing and Analyzing the LSM Compaction Design Space |
2021 |
VLDB |
6.7552936e-05 |
| 3,970 |
Spooky: Granulating LSM-Tree Compactions Correctly |
2022 |
VLDB |
6.5756727e-05 |
| 4,377 |
HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements |
2022 |
SIGMOD |
6.2331947e-05 |
| 4,404 |
TreeLine: An Update-In-Place Key-Value Store for Modern Storage |
2023 |
VLDB |
6.2052645e-05 |
| 4,920 |
On Performance Stability in LSM-based Storage Systems |
2020 |
VLDB |
5.8262404e-05 |
| 4,948 |
SplinterDB and Maplets: Improving the Tradeoffs in Key-Value Store Compaction Policy |
2023 |
SIGMOD |
5.810122e-05 |
| 5,313 |
Key-Value Storage Engines |
2020 |
SIGMOD |
5.5711707e-05 |
| 5,749 |
InfiniFilter: Expanding Filters to Infinity and Beyond |
2023 |
SIGMOD |
5.3420354e-05 |
| 5,801 |
Dissecting, Designing, and Optimizing LSM-based Data Stores |
2022 |
SIGMOD |
5.3217858e-05 |
| 5,868 |
GRF: A Global Range Filter for LSM-Trees with Shape Encoding |
2024 |
SIGMOD |
5.2928769e-05 |
| 5,920 |
Breaking Down Memory Walls: Adaptive Memory Management in LSM-based Storage Systems |
2021 |
VLDB |
5.2686888e-05 |
| 5,955 |
Spatial Independent Range Sampling |
2021 |
SIGMOD |
5.2539404e-05 |
| 6,186 |
Dotori: A Key-Value SSD Based KV Store |
2023 |
VLDB |
5.1616749e-05 |
| 6,394 |
Endure: A Robust Tuning Paradigm for LSM Trees Under Workload Uncertainty |
2022 |
VLDB |
5.0770427e-05 |
| 6,456 |
Toward a Better Understanding and Evaluation of Tree Structures on Flash SSDs |
2021 |
VLDB |
5.0505636e-05 |
| 7,092 |
Revisiting the Design of LSM-tree Based OLTP Storage Engine with Persistent Memory |
2021 |
VLDB |
4.83025e-05 |
| 7,167 |
TimeUnion: An Efficient Architecture with Unified Data Model for Timeseries Management Systems on Hybrid Cloud Storage |
2022 |
SIGMOD |
4.8075544e-05 |
| 7,623 |
Learning to Optimize LSM-trees: Towards A Reinforcement Learning based Key-Value Store for Dynamic Workloads |
2023 |
SIGMOD |
4.6890662e-05 |
| 7,812 |
CaaS-LSM: Compaction-as-a-Service for LSM-based Key-Value Stores in Storage Disaggregated Infrastructure |
2024 |
SIGMOD |
4.6411266e-05 |
| 8,011 |
CAMAL: Optimizing LSM-trees via Active Learning |
2024 |
SIGMOD |
4.6022693e-05 |
| 8,333 |
How to Grow an LSM-tree? Towards Bridging the Gap Between Theory and Practice |
2025 |
SIGMOD |
4.5390511e-05 |
| 8,426 |
Time Series Representation for Visualization in Apache IoTDB |
2024 |
SIGMOD |
4.5098472e-05 |
| 8,490 |
SA-LSM: Optimize Data Layout for LSM-tree Based Storage using Survival Analysis |
2022 |
VLDB |
4.494994e-05 |
| 8,524 |
Aleph Filter: To Infinity in Constant Time |
2024 |
VLDB |
4.4893996e-05 |
| 8,624 |
Limousine: Blending Learned and Classical Indexes to Self-Design Larger-than-Memory Cloud Storage Engines |
2024 |
SIGMOD |
4.4786127e-05 |
| 8,804 |
ArceKV: Towards Workload-driven LSM-compactions for Key-Value Store Under Dynamic Workloads |
2026 |
VLDB |
4.4424232e-05 |
| 8,876 |
MirrorKV: An Efficient Key-Value Store on Hybrid Cloud Storage with Balanced Performance of Compaction and Querying |
2023 |
SIGMOD |
4.4261814e-05 |
| 9,069 |
Structural Designs Meet Optimality: Exploring Optimized LSM-tree Structures in A Colossal Configuration Space |
2024 |
SIGMOD |
4.3983078e-05 |
| 9,322 |
Are Joins over LSM-trees Ready? Take RocksDB as an Example |
2025 |
VLDB |
4.351469e-05 |
| 9,390 |
Rethinking The Compaction Policies in LSM-trees |
2025 |
SIGMOD |
4.341433e-05 |
| 9,467 |
Disco: A Compact Index for LSM-trees |
2025 |
SIGMOD |
4.3309383e-05 |
| 9,529 |
Mnemosyne: Dynamic Workload-Aware BF Tuning via Accurate Statistics in LSM trees |
2025 |
SIGMOD |
4.3251912e-05 |
| 9,760 |
Practical Dynamic Extension for Sampling Indexes |
2023 |
SIGMOD |
4.2838028e-05 |
| 9,986 |
A Multi-tenant Relational OLTP Database at Salesforce |
2026 |
CIDR |
4.1905499e-05 |
| 10,063 |
Counting Is All You Need for Instant Tuple Discovery: Enabling Real-Time HTAP in Standalone DBMSs |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,176 |
Improving Range Scan Performance in LSM-trees with Group Caching |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,182 |
Making LSM-Tree-based Key-Value Store Practical and Efficient for Multi-Tenant Serverless Cloud Databases |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,567 |
BACH: Bridging Adjacency List and CSR Format using LSM-Trees for HGTAP Workloads |
2025 |
VLDB |
4.1905499e-05 |
| 11,534 |
The End of Moore’s Law and the Rise of The Data Processor |
2021 |
VLDB |
4.1905499e-05 |