| 71 |
How Good Are Query Optimizers, Really? |
2016 |
VLDB |
0.00059446482 |
| 183 |
Automatic Database Management System Tuning Through Large-scale Machine Learning |
2017 |
SIGMOD |
0.00036859633 |
| 371 |
Self-Driving Database Management Systems |
2017 |
CIDR |
0.00025382677 |
| 510 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.00021420477 |
| 517 |
AutoAdmin "What-if" Index Analysis Utility |
1998 |
SIGMOD |
0.00021193179 |
| 634 |
Bao: Making Learned Query Optimization Practical |
2021 |
SIGMOD |
0.00018844568 |
| 661 |
Adaptive Self-Tuning Memory in DB2 |
2006 |
VLDB |
0.00018488168 |
| 704 |
Query-based Workload Forecasting for Self-Driving Database Management Systems |
2018 |
SIGMOD |
0.00017785557 |
| 779 |
QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning |
2019 |
VLDB |
0.00016719473 |
| 876 |
Plan-Structured Deep Neural Network Models for Query Performance Prediction |
2019 |
VLDB |
0.00015660534 |
| 1,018 |
Automatic Physical Database Tuning: A Relaxation-based Approach |
2005 |
SIGMOD |
0.00014626746 |
| 1,856 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00010319105 |
| 1,866 |
ReAcTable: Enhancing ReAct for Table Question Answering |
2024 |
VLDB |
0.00010265592 |
| 1,953 |
D-Bot: Database Diagnosis System using Large Language Models |
2024 |
VLDB |
9.9701097e-05 |
| 2,022 |
Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms |
2020 |
VLDB |
9.7623022e-05 |
| 2,937 |
DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems |
2021 |
VLDB |
7.8552033e-05 |
| 3,131 |
Why TPC Is Not Enough: An Analysis of the Amazon Redshift Fleet |
2024 |
VLDB |
7.5054309e-05 |
| 3,144 |
Active Learning for ML Enhanced Database Systems |
2020 |
SIGMOD |
7.4844943e-05 |
| 3,167 |
QueryFormer: A Tree Transformer Model for Query Plan Representation |
2022 |
VLDB |
7.4561078e-05 |
| 3,403 |
ELPIS: Graph-Based Similarity Search for Scalable Data Science |
2023 |
VLDB |
7.1338786e-05 |
| 3,435 |
Real-time Workload Pattern Analysis for Large-scale Cloud Databases |
2023 |
VLDB |
7.0946114e-05 |
| 3,465 |
LLM-R2: A Large Language Model Enhanced Rule-based Rewrite System for Boosting Query Efficiency |
2025 |
VLDB |
7.0668293e-05 |
| 3,655 |
Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation |
2022 |
VLDB |
6.8723042e-05 |
| 3,777 |
Instance-Optimized Data Layouts for Cloud Analytics Workloads |
2021 |
SIGMOD |
6.7713324e-05 |
| 3,819 |
Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction |
2022 |
VLDB |
6.7267885e-05 |
| 4,180 |
LlamaTune: Sample-Efficient DBMS Configuration Tuning |
2022 |
VLDB |
6.3725334e-05 |
| 4,216 |
Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation |
2021 |
VLDB |
6.3448176e-05 |
| 4,413 |
Robust Query Driven Cardinality Estimation under Changing Workloads |
2023 |
VLDB |
6.1989918e-05 |
| 4,464 |
LOGER: A Learned Optimizer towards Generating Efficient and Robust Query Execution Plans |
2023 |
VLDB |
6.1552798e-05 |
| 4,587 |
MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems |
2021 |
SIGMOD |
6.0594195e-05 |
| 4,621 |
Automated Generation of Materialized Views in Oracle |
2020 |
VLDB |
6.036749e-05 |
| 4,730 |
UDO: Universal Database Optimization using Reinforcement Learning |
2021 |
VLDB |
5.9604983e-05 |
| 4,762 |
METER: A Dynamic Concept Adaptation Framework for Online Anomaly Detection |
2024 |
VLDB |
5.9338398e-05 |
| 4,908 |
Combining Small Language Models and Large Language Models for Zero-Shot NL2SQL |
2024 |
VLDB |
5.835596e-05 |
| 5,339 |
LEON: A New Framework for ML-Aided Query Optimization |
2023 |
VLDB |
5.5596755e-05 |
| 5,343 |
Learned Index Benefits: Machine Learning Based Index Performance Estimation |
2022 |
VLDB |
5.5582234e-05 |
| 5,463 |
The RLR-Tree: A Reinforcement Learning Based R-Tree for Spatial Data |
2023 |
SIGMOD |
5.4920768e-05 |
| 5,528 |
Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts |
2022 |
SIGMOD |
5.4571136e-05 |
| 5,639 |
Analyzing the Impact of Cardinality Estimation on Execution Plans in Microsoft SQL Server |
2023 |
VLDB |
5.3972261e-05 |
| 5,654 |
AutoSteer: Learned Query Optimization for Any SQL Database |
2023 |
VLDB |
5.3882121e-05 |
| 5,673 |
Budget-aware Index Tuning with Reinforcement Learning |
2022 |
SIGMOD |
5.3789277e-05 |
| 5,834 |
An Efficient Transfer Learning Based Configuration Adviser for Database Tuning |
2024 |
VLDB |
5.3082111e-05 |
| 6,113 |
Doppler: Automated SKU Recommendation in Migrating SQL Workloads to the Cloud |
2022 |
VLDB |
5.2006495e-05 |
| 6,374 |
Dear User-Defined Functions, Inlining isn't working out so great for us. Let's try batching to make our relationship work. Sincerely, SQL |
2024 |
CIDR |
5.0874998e-05 |
| 6,376 |
A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning |
2023 |
SIGMOD |
5.0861082e-05 |
| 6,564 |
Automatic Database Configuration Debugging using Retrieval-Augmented Language Models |
2025 |
SIGMOD |
5.0037892e-05 |
| 6,687 |
How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks |
2025 |
SIGMOD |
4.957987e-05 |
| 7,009 |
Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective |
2024 |
VLDB |
4.8597992e-05 |
| 7,220 |
Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation |
2023 |
SIGMOD |
4.7926382e-05 |
| 7,308 |
DBMind: A Self-Driving Platform in openGauss |
2021 |
VLDB |
4.7620018e-05 |