| 4,063 |
The Art of Balance: A RateupDB Experience of Building a CPU/GPU Hybrid Database Product |
2021 |
VLDB |
6.812902e-05 |
| 4,101 |
Towards Dynamic and Safe Configuration Tuning for Cloud Databases |
2022 |
SIGMOD |
6.7930727e-05 |
| 4,202 |
Kepler: Robust Learning for Faster Parametric Query Optimization |
2023 |
SIGMOD |
6.7258607e-05 |
| 4,302 |
A Method for Optimizing Opaque Filter Queries |
2020 |
SIGMOD |
6.6614501e-05 |
| 4,315 |
ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads |
2024 |
VLDB |
6.6545412e-05 |
| 4,459 |
Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts |
2022 |
SIGMOD |
6.5757572e-05 |
| 4,479 |
Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process |
2022 |
SIGMOD |
6.5665703e-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 |
| 4,683 |
AutoSteer: Learned Query Optimization for Any SQL Database |
2023 |
VLDB |
6.4545989e-05 |
| 4,703 |
Learned Cardinality Estimation for Similarity Queries |
2021 |
SIGMOD |
6.4458272e-05 |
| 4,720 |
PreQR: Pre-training Representation for SQL Understanding |
2022 |
SIGMOD |
6.4353798e-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 |
| 4,792 |
Learned Approximate Query Processing: Make it Light, Accurate and Fast |
2021 |
CIDR |
6.4010108e-05 |
| 4,797 |
LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems |
2022 |
SIGMOD |
6.3978116e-05 |
| 4,882 |
LpBound: Pessimistic Cardinality Estimation using ℓp-Norms of Degree Sequences |
2025 |
SIGMOD |
6.3565046e-05 |
| 4,915 |
Can Learned Models Replace Hash Functions? |
2023 |
VLDB |
6.3452789e-05 |
| 4,971 |
Debunking the Myth of Join Ordering: Toward Robust SQL Analytics |
2025 |
SIGMOD |
6.3209003e-05 |
| 5,029 |
COMPASS: Online Sketch-based Query Optimization for In-Memory Databases |
2021 |
SIGMOD |
6.2952031e-05 |
| 5,044 |
Analyzing the Impact of Cardinality Estimation on Execution Plans in Microsoft SQL Server |
2023 |
VLDB |
6.2888728e-05 |
| 5,075 |
SafeBound: A Practical System for Generating Cardinality Bounds |
2023 |
SIGMOD |
6.2721634e-05 |
| 5,126 |
Steering Query Optimizers: A Practical Take on Big Data Workloads |
2021 |
SIGMOD |
6.2493606e-05 |
| 5,153 |
Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach |
2020 |
SIGMOD |
6.2375324e-05 |
| 5,237 |
SAM: Database Generation from Query Workloads with Supervised Autoregressive Models |
2022 |
SIGMOD |
6.2027113e-05 |
| 5,245 |
FASTgres: Making Learned Query Optimizer Hinting Effective |
2023 |
VLDB |
6.1995935e-05 |
| 5,453 |
Eraser: Eliminating Performance Regression on Learned Query Optimizer |
2024 |
VLDB |
6.1077838e-05 |
| 5,457 |
Sample-Efficient Cardinality Estimation Using Geometric Deep Learning |
2024 |
VLDB |
6.1058928e-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 |
| 5,713 |
PilotScope: Steering Databases with Machine Learning Drivers |
2024 |
VLDB |
6.0090633e-05 |
| 5,728 |
Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data |
2023 |
SIGMOD |
5.9979958e-05 |
| 5,837 |
Pre-training Summarization Models of Structured Datasets for Cardinality Estimation |
2022 |
VLDB |
5.9600736e-05 |
| 5,841 |
Joins on Samples: A Theoretical Guide for Practitioners |
2020 |
VLDB |
5.9569427e-05 |
| 5,854 |
Modeling Shifting Workloads for Learned Database Systems |
2024 |
SIGMOD |
5.9520525e-05 |
| 5,926 |
Quantum-Inspired Digital Annealing for Join Ordering |
2024 |
VLDB |
5.9282142e-05 |
| 5,982 |
Towards instance-optimized data systems |
2021 |
VLDB |
5.9096991e-05 |
| 6,095 |
From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems |
2019 |
SIGMOD |
5.8706416e-05 |
| 6,113 |
Expand your Training Limits! Generating Training Data for ML-based Data Management |
2021 |
SIGMOD |
5.8662826e-05 |
| 6,121 |
Breaking It Down: An In-depth Study of Index Advisors |
2024 |
VLDB |
5.863893e-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 |
| 6,485 |
Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks |
2024 |
SIGMOD |
5.7525455e-05 |
| 6,672 |
Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation |
2023 |
SIGMOD |
5.6975871e-05 |
| 6,725 |
Simple Adaptive Query Processing vs. Learned Query Optimizers: Observations and Analysis |
2023 |
VLDB |
5.6826988e-05 |
| 6,768 |
Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities |
2022 |
SIGMOD |
5.6693759e-05 |
| 6,812 |
dbET: Execution Time Distribution-based Plan Selection |
2023 |
SIGMOD |
5.6597129e-05 |
| 6,840 |
ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation |
2024 |
SIGMOD |
5.6513231e-05 |
| 6,906 |
LPLM: A Neural Language Model for Cardinality Estimation of LIKE-Queries |
2024 |
SIGMOD |
5.634971e-05 |
| 7,175 |
Learning to Sample: Counting with Complex Queries |
2020 |
VLDB |
5.5779755e-05 |