| 101 |
The Case for Learned Index Structures |
2018 |
SIGMOD |
0.00049778866 |
| 183 |
Automatic Database Management System Tuning Through Large-scale Machine Learning |
2017 |
SIGMOD |
0.00036859633 |
| 281 |
LinkBench: a Database Benchmark Based on the Facebook Social Graph |
2013 |
SIGMOD |
0.00029084275 |
| 371 |
Self-Driving Database Management Systems |
2017 |
CIDR |
0.00025382677 |
| 379 |
bLSM: A General Purpose Log Structured Merge Tree |
2012 |
SIGMOD |
0.00024954332 |
| 423 |
Tuning Database Configuration Parameters with iTuned |
2009 |
VLDB |
0.00023628474 |
| 510 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.00021420477 |
| 606 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00019251186 |
| 608 |
Monkey: Optimal Navigable Key-Value Store |
2017 |
SIGMOD |
0.00019233548 |
| 779 |
QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning |
2019 |
VLDB |
0.00016719473 |
| 804 |
An End-to-End Learning-based Cost Estimator |
2020 |
VLDB |
0.0001643674 |
| 876 |
Plan-Structured Deep Neural Network Models for Query Performance Prediction |
2019 |
VLDB |
0.00015660534 |
| 1,169 |
SuRF: Practical Range Query Filtering with Fast Succinct Tries |
2018 |
SIGMOD |
0.00013530267 |
| 1,239 |
Selectivity Estimation for Range Predicates using Lightweight Models |
2019 |
VLDB |
0.00013091459 |
| 1,309 |
Dostoevsky: Better Space-Time Trade-Offs for LSM-Tree Based Key-Value Stores via Adaptive Removal of Superfluous Merging |
2018 |
SIGMOD |
0.00012655712 |
| 1,368 |
SlimDB: A Space-Efficient Key-Value Storage Engine For Semi-Sorted Data |
2017 |
VLDB |
0.0001235708 |
| 1,616 |
Realtime Data Processing at Facebook |
2016 |
SIGMOD |
0.00011133818 |
| 1,699 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00010848882 |
| 1,816 |
An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems |
2021 |
VLDB |
0.00010438512 |
| 1,932 |
X-Engine: An Optimized Storage Engine for Large-scale E-commerce Transaction Processing |
2019 |
SIGMOD |
0.00010050776 |
| 1,957 |
Compaction management in distributed key-value datastores |
2015 |
VLDB |
9.961151e-05 |
| 2,112 |
The Log-Structured Merge-Bush & the Wacky Continuum |
2019 |
SIGMOD |
9.5244583e-05 |
| 2,595 |
WeTune: Automatic Discovery and Verification of Query Rewrite Rules |
2022 |
SIGMOD |
8.4725961e-05 |
| 2,606 |
Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn |
2019 |
CIDR |
8.4621503e-05 |
| 2,797 |
Chucky: A Succinct Cuckoo Filter for LSM-Tree |
2021 |
SIGMOD |
8.1116755e-05 |
| 3,144 |
Active Learning for ML Enhanced Database Systems |
2020 |
SIGMOD |
7.4844943e-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 |
| 3,567 |
Accordion: Better Memory Organization for LSM Key-Value Stores |
2018 |
VLDB |
6.9606988e-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 |
| 4,216 |
Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation |
2021 |
VLDB |
6.3448176e-05 |
| 4,227 |
Cosine: A Cloud-Cost Optimized Self-Designing Key-Value Storage Engine |
2022 |
VLDB |
6.3381409e-05 |
| 4,572 |
Leaper: A Learned Prefetcher for Cache Invalidation in LSM-tree based Storage Engines |
2020 |
VLDB |
6.068399e-05 |
| 4,587 |
MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems |
2021 |
SIGMOD |
6.0594195e-05 |
| 4,755 |
Optimization for Active Learning-based Interactive Database Exploration |
2019 |
VLDB |
5.9375171e-05 |
| 4,836 |
Proteus: A Self-Designing Range Filter |
2022 |
SIGMOD |
5.8849277e-05 |
| 5,367 |
LogKV: Exploiting Key-Value Stores for Event Log Processing |
2013 |
CIDR |
5.5461097e-05 |
| 5,463 |
The RLR-Tree: A Reinforcement Learning Based R-Tree for Spatial Data |
2023 |
SIGMOD |
5.4920768e-05 |
| 5,543 |
Lightweight Cardinality Estimation in LSM-based Systems |
2018 |
SIGMOD |
5.4486922e-05 |
| 5,801 |
Dissecting, Designing, and Optimizing LSM-based Data Stores |
2022 |
SIGMOD |
5.3217858e-05 |
| 5,920 |
Breaking Down Memory Walls: Adaptive Memory Management in LSM-based Storage Systems |
2021 |
VLDB |
5.2686888e-05 |
| 6,394 |
Endure: A Robust Tuning Paradigm for LSM Trees Under Workload Uncertainty |
2022 |
VLDB |
5.0770427e-05 |
| 7,623 |
Learning to Optimize LSM-trees: Towards A Reinforcement Learning based Key-Value Store for Dynamic Workloads |
2023 |
SIGMOD |
4.6890662e-05 |
| 8,036 |
Tastes Great! Less Filling! High Performance and Accurate Training Data Collection for Self-Driving Database Management Systems |
2022 |
SIGMOD |
4.5965825e-05 |
| 9,069 |
Structural Designs Meet Optimality: Exploring Optimized LSM-tree Structures in A Colossal Configuration Space |
2024 |
SIGMOD |
4.3983078e-05 |