| 355 |
Bao: Making Learned Query Optimization Practical |
2021 |
SIGMOD |
0.00020146245 |
| 453 |
An End-to-End Learning-based Cost Estimator |
2020 |
VLDB |
0.0001801482 |
| 1,400 |
Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms |
2020 |
VLDB |
0.00010759064 |
| 1,513 |
DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems |
2021 |
VLDB |
0.00010394557 |
| 1,529 |
Updatable Learned Index with Precise Positions |
2021 |
VLDB |
0.00010320909 |
| 2,169 |
QueryFormer: A Tree Transformer Model for Query Plan Representation |
2022 |
VLDB |
8.9151935e-05 |
| 2,190 |
Lero: A Learning-to-Rank Query Optimizer |
2023 |
VLDB |
8.8848923e-05 |
| 2,290 |
Active Learning for ML Enhanced Database Systems |
2020 |
SIGMOD |
8.6813363e-05 |
| 2,389 |
A Learned Query Rewrite System using Monte Carlo Tree Search |
2022 |
VLDB |
8.5228689e-05 |
| 2,619 |
Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction |
2022 |
VLDB |
8.1985665e-05 |
| 2,696 |
Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection |
2022 |
VLDB |
8.1068354e-05 |
| 2,768 |
Query Performance Prediction for Concurrent Queries using Graph Embedding |
2020 |
VLDB |
8.0199086e-05 |
| 2,852 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
7.9201312e-05 |
| 2,913 |
AI Meets Database: AI4DB and DB4AI |
2021 |
SIGMOD |
7.855786e-05 |
| 3,282 |
Estimating Cardinalities with Deep Sketches |
2019 |
SIGMOD |
7.4491295e-05 |
| 3,328 |
Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift |
2023 |
SIGMOD |
7.4094448e-05 |
| 3,575 |
Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation |
2021 |
VLDB |
7.1769215e-05 |
| 3,687 |
openGauss: An Autonomous Database System |
2021 |
VLDB |
7.0797286e-05 |
| 3,709 |
Stable Learned Bloom Filters for Data Streams |
2020 |
VLDB |
7.0586477e-05 |
| 3,959 |
MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems |
2021 |
SIGMOD |
6.8804723e-05 |
| 4,247 |
LEON: A New Framework for ML-Aided Query Optimization |
2023 |
VLDB |
6.6920059e-05 |
| 4,549 |
One Model to Rule them All: Towards Zero-Shot Learning for Databases |
2022 |
CIDR |
6.5328866e-05 |
| 4,641 |
How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks |
2025 |
SIGMOD |
6.4739208e-05 |
| 4,726 |
Learned Index Benefits: Machine Learning Based Index Performance Estimation |
2022 |
VLDB |
6.4329878e-05 |
| 4,765 |
Machine Learning for Databases |
2021 |
VLDB |
6.4166895e-05 |
| 4,833 |
Stage: Query Execution Time Prediction in Amazon Redshift |
2024 |
SIGMOD |
6.3834856e-05 |
| 5,043 |
Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing |
2022 |
VLDB |
6.28918e-05 |
| 5,153 |
Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach |
2020 |
SIGMOD |
6.2375324e-05 |
| 5,211 |
Database Workload Characterization with Query Plan Encoders |
2022 |
VLDB |
6.2141929e-05 |
| 5,453 |
Eraser: Eliminating Performance Regression on Learned Query Optimizer |
2024 |
VLDB |
6.1077838e-05 |
| 5,484 |
A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies |
2024 |
VLDB |
6.0980944e-05 |
| 5,687 |
HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning |
2023 |
VLDB |
6.0201937e-05 |
| 5,854 |
Modeling Shifting Workloads for Learned Database Systems |
2024 |
SIGMOD |
5.9520525e-05 |
| 6,113 |
Expand your Training Limits! Generating Training Data for ML-based Data Management |
2021 |
SIGMOD |
5.8662826e-05 |
| 6,158 |
Rethinking Learned Cost Models: Why Start from Scratch? |
2023 |
SIGMOD |
5.8518237e-05 |
| 6,402 |
A Unified Transferable Model for ML-Enhanced DBMS |
2022 |
CIDR |
5.7800842e-05 |
| 7,169 |
Cost-Intelligent Data Analytics in the Cloud |
2024 |
CIDR |
5.5789764e-05 |
| 7,238 |
Refactoring Index Tuning Process with Benefit Estimation |
2024 |
VLDB |
5.5624225e-05 |
| 7,363 |
Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD |
2024 |
VLDB |
5.5279826e-05 |
| 7,483 |
T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees |
2025 |
SIGMOD |
5.5007125e-05 |
| 7,561 |
Learned Offline Query Planning via Bayesian Optimization |
2025 |
SIGMOD |
5.4784915e-05 |
| 7,715 |
Tastes Great! Less Filling! High Performance and Accurate Training Data Collection for Self-Driving Database Management Systems |
2022 |
SIGMOD |
5.4556951e-05 |
| 7,925 |
CAMAL: Optimizing LSM-trees via Active Learning |
2024 |
SIGMOD |
5.4086685e-05 |
| 7,997 |
The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions |
2024 |
VLDB |
5.3938336e-05 |
| 8,589 |
Robust and Budget-Constrained Encoding Configurations for In-Memory Database Systems |
2022 |
VLDB |
5.2937865e-05 |
| 8,657 |
LIMAO: A Framework for Lifelong Modular Learned Query Optimization |
2025 |
VLDB |
5.2790784e-05 |
| 8,902 |
Tiresias: Enabling Predictive Autonomous Storage and Indexing |
2022 |
VLDB |
5.2387388e-05 |
| 8,989 |
Conformal Prediction for Verifiable Learned Query Optimization |
2025 |
VLDB |
5.2304457e-05 |
| 9,011 |
Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries |
2025 |
VLDB |
5.2238303e-05 |
| 9,143 |
Check Out the Big Brain on BRAD: Simplifying Cloud Data Processing with Learned Automated Data Meshes |
2023 |
VLDB |
5.2074327e-05 |