| 18 |
How Good Are Query Optimizers, Really? |
2016 |
VLDB |
0.00059284255 |
| 86 |
Automatic Database Management System Tuning Through Large-scale Machine Learning |
2017 |
SIGMOD |
0.00035316107 |
| 234 |
Self-Driving Database Management Systems |
2017 |
CIDR |
0.00023810722 |
| 334 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.00020875082 |
| 378 |
Bao: Making Learned Query Optimization Practical |
2021 |
SIGMOD |
0.00019638121 |
| 387 |
AutoAdmin "What-if" Index Analysis Utility |
1998 |
SIGMOD |
0.00019442332 |
| 461 |
Query-based Workload Forecasting for Self-Driving Database Management Systems |
2018 |
SIGMOD |
0.00018068441 |
| 498 |
QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning |
2019 |
VLDB |
0.00017440583 |
| 523 |
Adaptive Self-Tuning Memory in DB2 |
2006 |
VLDB |
0.00017133451 |
| 563 |
Plan-Structured Deep Neural Network Models for Query Performance Prediction |
2019 |
VLDB |
0.0001650812 |
| 768 |
Automatic Physical Database Tuning: A Relaxation-based Approach |
2005 |
SIGMOD |
0.00014173242 |
| 1,279 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00011361878 |
| 1,481 |
Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms |
2020 |
VLDB |
0.00010644613 |
| 1,832 |
DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems |
2021 |
VLDB |
9.6607418e-05 |
| 1,920 |
D-Bot: Database Diagnosis System using Large Language Models |
2024 |
VLDB |
9.4846185e-05 |
| 1,981 |
ReAcTable: Enhancing ReAct for Table Question Answering |
2024 |
VLDB |
9.3579557e-05 |
| 2,313 |
Active Learning for ML Enhanced Database Systems |
2020 |
SIGMOD |
8.762627e-05 |
| 2,355 |
QueryFormer: A Tree Transformer Model for Query Plan Representation |
2022 |
VLDB |
8.7022189e-05 |
| 2,408 |
Why TPC Is Not Enough: An Analysis of the Amazon Redshift Fleet |
2024 |
VLDB |
8.6154404e-05 |
| 2,534 |
ELPIS: Graph-Based Similarity Search for Scalable Data Science |
2023 |
VLDB |
8.4561875e-05 |
| 2,553 |
LLM-R^2: A Large Language Model Enhanced Rule-based Rewrite System for Boosting Query Efficiency |
2025 |
VLDB |
8.4283807e-05 |
| 2,740 |
Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation |
2022 |
VLDB |
8.1855759e-05 |
| 2,844 |
Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction |
2022 |
VLDB |
8.0608767e-05 |
| 3,035 |
Instance-Optimized Data Layouts for Cloud Analytics Workloads |
2021 |
SIGMOD |
7.8297746e-05 |
| 3,338 |
Robust Query Driven Cardinality Estimation under Changing Workloads |
2023 |
VLDB |
7.5068221e-05 |
| 3,343 |
LlamaTune: Sample-Efficient DBMS Configuration Tuning |
2022 |
VLDB |
7.4983591e-05 |
| 3,516 |
LOGER: A Learned Optimizer towards Generating Efficient and Robust Query Execution Plans |
2023 |
VLDB |
7.3524442e-05 |
| 3,586 |
Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation |
2021 |
VLDB |
7.2834069e-05 |
| 3,787 |
Combining Small Language Models and Large Language Models for Zero-Shot NL2SQL |
2024 |
VLDB |
7.1249098e-05 |
| 3,926 |
UDO: Universal Database Optimization using Reinforcement Learning |
2021 |
VLDB |
7.0128068e-05 |
| 3,961 |
MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems |
2021 |
SIGMOD |
6.987575e-05 |
| 4,101 |
Automated Generation of Materialized Views in Oracle |
2020 |
VLDB |
6.9009734e-05 |
| 4,398 |
Real-time Workload Pattern Analysis for Large-scale Cloud Databases |
2023 |
VLDB |
6.7248611e-05 |
| 4,434 |
LEON: A New Framework for ML-Aided Query Optimization |
2023 |
VLDB |
6.7079088e-05 |
| 4,612 |
Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts |
2022 |
SIGMOD |
6.6072026e-05 |
| 4,643 |
Learned Index Benefits: Machine Learning Based Index Performance Estimation |
2022 |
VLDB |
6.5907466e-05 |
| 4,751 |
The RLR-Tree: A Reinforcement Learning Based R-Tree for Spatial Data |
2023 |
SIGMOD |
6.5241784e-05 |
| 4,814 |
METER: A Dynamic Concept Adaptation Framework for Online Anomaly Detection |
2024 |
VLDB |
6.4955135e-05 |
| 4,929 |
AutoSteer: Learned Query Optimization for Any SQL Database |
2023 |
VLDB |
6.4423294e-05 |
| 5,010 |
Analyzing the Impact of Cardinality Estimation on Execution Plans in Microsoft SQL Server |
2023 |
VLDB |
6.4023732e-05 |
| 5,091 |
Budget-aware Index Tuning with Reinforcement Learning |
2022 |
SIGMOD |
6.3669569e-05 |
| 5,171 |
An Efficient Transfer Learning Based Configuration Adviser for Database Tuning |
2024 |
VLDB |
6.3347618e-05 |
| 5,856 |
Automatic Database Configuration Debugging using Retrieval-Augmented Language Models |
2025 |
SIGMOD |
6.0644656e-05 |
| 6,015 |
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 |
6.008272e-05 |
| 6,088 |
How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks |
2025 |
SIGMOD |
5.9813965e-05 |
| 6,177 |
Doppler: Automated SKU Recommendation in Migrating SQL Workloads to the Cloud |
2022 |
VLDB |
5.9496208e-05 |
| 6,271 |
Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective |
2024 |
VLDB |
5.9326197e-05 |
| 6,543 |
Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation |
2023 |
SIGMOD |
5.8461929e-05 |
| 6,600 |
A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning |
2023 |
SIGMOD |
5.8250114e-05 |
| 6,997 |
E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model |
2025 |
VLDB |
5.7300324e-05 |