| 362 |
Bao: Making Learned Query Optimization Practical |
2021 |
SIGMOD |
0.00019989474 |
| 1,250 |
DB-BERT: A Database Tuning Tool that "Reads the Manual" |
2022 |
SIGMOD |
0.00011339256 |
| 1,397 |
Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms |
2020 |
VLDB |
0.00010789242 |
| 1,515 |
DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems |
2021 |
VLDB |
0.00010417728 |
| 1,516 |
Automatically Indexing Millions of Databases in Microsoft Azure SQL Database |
2019 |
SIGMOD |
0.00010402594 |
| 2,207 |
Magpie: Python at Speed and Scale using Cloud Backends |
2021 |
CIDR |
8.8487039e-05 |
| 2,210 |
Lero: A Learning-to-Rank Query Optimizer |
2023 |
VLDB |
8.8257742e-05 |
| 2,250 |
QueryFormer: A Tree Transformer Model for Query Plan Representation |
2022 |
VLDB |
8.7533306e-05 |
| 2,275 |
Active Learning for ML Enhanced Database Systems |
2020 |
SIGMOD |
8.7090584e-05 |
| 3,563 |
Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift |
2023 |
SIGMOD |
7.2042148e-05 |
| 3,645 |
UDO: Universal Database Optimization using Reinforcement Learning |
2021 |
VLDB |
7.1397796e-05 |
| 3,949 |
Deploying a Steered Query Optimizer in Production at Microsoft |
2022 |
SIGMOD |
6.9052796e-05 |
| 4,202 |
Kepler: Robust Learning for Faster Parametric Query Optimization |
2023 |
SIGMOD |
6.7374091e-05 |
| 4,258 |
LEON: A New Framework for ML-Aided Query Optimization |
2023 |
VLDB |
6.6994722e-05 |
| 4,457 |
Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process |
2022 |
SIGMOD |
6.5913732e-05 |
| 4,711 |
Learned Index Benefits: Machine Learning Based Index Performance Estimation |
2022 |
VLDB |
6.4573842e-05 |
| 4,741 |
Machine Learning for Databases |
2021 |
VLDB |
6.4410027e-05 |
| 4,968 |
Budget-aware Index Tuning with Reinforcement Learning |
2022 |
SIGMOD |
6.3348803e-05 |
| 5,126 |
Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach |
2020 |
SIGMOD |
6.261175e-05 |
| 5,158 |
Facilitating SQL Query Composition and Analysis |
2020 |
SIGMOD |
6.2492918e-05 |
| 5,194 |
Database Workload Characterization with Query Plan Encoders |
2022 |
VLDB |
6.2353557e-05 |
| 5,214 |
Stage: Query Execution Time Prediction in Amazon Redshift |
2024 |
SIGMOD |
6.2248104e-05 |
| 5,456 |
Eraser: Eliminating Performance Regression on Learned Query Optimizer |
2024 |
VLDB |
6.1239873e-05 |
| 5,481 |
A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies |
2024 |
VLDB |
6.1125124e-05 |
| 5,674 |
HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning |
2023 |
VLDB |
6.0430252e-05 |
| 5,871 |
PilotScope: Steering Databases with Machine Learning Drivers |
2024 |
VLDB |
5.9639223e-05 |
| 5,902 |
Yannakakis+: Practical Acyclic Query Evaluation with Theoretical Guarantees |
2025 |
SIGMOD |
5.9536872e-05 |
| 5,974 |
Towards instance-optimized data systems |
2021 |
VLDB |
5.9305575e-05 |
| 6,105 |
Breaking It Down: An In-depth Study of Index Advisors |
2024 |
VLDB |
5.8860941e-05 |
| 6,141 |
Expand your Training Limits! Generating Training Data for ML-based Data Management |
2021 |
SIGMOD |
5.8733296e-05 |
| 6,726 |
A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning |
2023 |
SIGMOD |
5.6948731e-05 |
| 6,753 |
Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities |
2022 |
SIGMOD |
5.6904085e-05 |
| 7,217 |
Refactoring Index Tuning Process with Benefit Estimation |
2024 |
VLDB |
5.5834823e-05 |
| 7,236 |
RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems |
2025 |
VLDB |
5.5790509e-05 |
| 7,363 |
PerfGuard: Deploying ML-for-Systems without Performance Regressions, Almost! |
2021 |
VLDB |
5.5418564e-05 |
| 7,764 |
DBG-PT: A Large Language Model Assisted Query Performance Regression Debugger |
2024 |
VLDB |
5.4564979e-05 |
| 7,806 |
Machine Learning for Cloud Data Systems: the Progress so far and the Path Forward |
2021 |
VLDB |
5.4500623e-05 |
| 7,900 |
DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning |
2022 |
VLDB |
5.4303143e-05 |
| 7,977 |
The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions |
2024 |
VLDB |
5.4142519e-05 |
| 8,771 |
Automatic Indexing in Oracle |
2025 |
VLDB |
5.2806451e-05 |
| 9,671 |
Robustness of Updatable Learning-based Index Advisors against Poisoning Attack |
2024 |
SIGMOD |
5.1448657e-05 |
| 9,720 |
APQO: An Adaptive Framework for Parametric Query Optimization |
2026 |
SIGMOD |
5.1349531e-05 |
| 9,781 |
Optimizing Dataflow Systems for Scalable Interactive Visualization |
2024 |
SIGMOD |
5.1300393e-05 |
| 9,790 |
Wii: Dynamic Budget Reallocation In Index Tuning |
2024 |
SIGMOD |
5.1260323e-05 |
| 9,919 |
Waffle: In-memory Grid Index for Moving Objects with Reinforcement Learning-based Configuration Tuning System |
2022 |
VLDB |
5.1103839e-05 |
| 9,956 |
Graph Transformers for Query Plan Representation: Potentials and Challenges |
2025 |
VLDB |
5.1038322e-05 |
| 10,287 |
AdaChain: A Learned Adaptive Blockchain |
2023 |
VLDB |
5.0448662e-05 |
| 10,290 |
This is Going to Sound Crazy, But What If We Used Large Language Models to Boost Automatic Database Tuning Algorithms By Leveraging Prior History? We Will Find Better Configurations More Quickly Than Retraining From Scratch! |
2026 |
SIGMOD |
5.0431863e-05 |
| 10,297 |
Wred: Workload Reduction for Scalable Index Tuning |
2024 |
SIGMOD |
5.0430432e-05 |
| 10,412 |
Are Learned DBMS Components Robust to Workload Drift?: [Experiments & Analysis] |
2026 |
SIGMOD |
4.9793485e-05 |