| 84 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00035920657 |
| 309 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.0002143249 |
| 411 |
QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning |
2019 |
VLDB |
0.0001874043 |
| 550 |
SageDB: A Learned Database System |
2019 |
CIDR |
0.00016525249 |
| 1,132 |
Qd-tree: Learning Data Layouts for Big Data Analytics |
2020 |
SIGMOD |
0.00011873466 |
| 1,156 |
QuickSel: Quick Selectivity Learning with Mixture Models |
2020 |
SIGMOD |
0.00011759683 |
| 1,238 |
DB-BERT: A Database Tuning Tool that "Reads the Manual" |
2022 |
SIGMOD |
0.00011375179 |
| 1,282 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00011197535 |
| 1,294 |
An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems |
2021 |
VLDB |
0.00011129451 |
| 1,436 |
Towards a Learning Optimizer for Shared Clouds |
2019 |
VLDB |
0.00010658836 |
| 1,509 |
Cloud-Native Database Systems at Alibaba: Opportunities and Challenges |
2019 |
VLDB |
0.00010415166 |
| 1,529 |
Updatable Learned Index with Precise Positions |
2021 |
VLDB |
0.00010320909 |
| 1,611 |
The Data Calculator*: Data Structure Design and Cost Synthesis from First Principles and Learned Cost Models |
2018 |
SIGMOD |
0.00010066379 |
| 1,700 |
Black or White? How to Develop an AutoTuner for Memory-based Analytics |
2020 |
SIGMOD |
9.8224761e-05 |
| 1,771 |
Diagnosing Root Causes of Intermittent Slow Queries in Cloud Databases |
2020 |
VLDB |
9.6775181e-05 |
| 1,900 |
Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn |
2019 |
CIDR |
9.3926585e-05 |
| 2,009 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
9.1813272e-05 |
| 2,227 |
GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization |
2024 |
VLDB |
8.7924681e-05 |
| 2,290 |
Active Learning for ML Enhanced Database Systems |
2020 |
SIGMOD |
8.6813363e-05 |
| 2,572 |
ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases |
2021 |
SIGMOD |
8.2581875e-05 |
| 2,584 |
Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation |
2021 |
VLDB |
8.2435322e-05 |
| 2,772 |
Instance-Optimized Data Layouts for Cloud Analytics Workloads |
2021 |
SIGMOD |
8.0148928e-05 |
| 2,779 |
Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation |
2022 |
VLDB |
8.0085666e-05 |
| 2,891 |
Optimal Column Layout for Hybrid Workloads |
2019 |
VLDB |
7.887378e-05 |
| 2,913 |
AI Meets Database: AI4DB and DB4AI |
2021 |
SIGMOD |
7.855786e-05 |
| 2,929 |
iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases |
2019 |
VLDB |
7.830745e-05 |
| 2,995 |
Panda: Performance Debugging for Databases using LLM Agents |
2024 |
CIDR |
7.7556154e-05 |
| 3,037 |
Autoscaling Tiered Cloud Storage in Anna |
2019 |
VLDB |
7.7086155e-05 |
| 3,057 |
LlamaTune: Sample-Efficient DBMS Configuration Tuning |
2022 |
VLDB |
7.6865211e-05 |
| 3,172 |
CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions |
2021 |
VLDB |
7.5556865e-05 |
| 3,328 |
Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift |
2023 |
SIGMOD |
7.4094448e-05 |
| 3,408 |
Native Store Extension for SAP HANA |
2019 |
VLDB |
7.3093844e-05 |
| 3,443 |
A Demonstration of the OtterTune Automatic Database Management System Tuning Service |
2018 |
VLDB |
7.2781031e-05 |
| 3,486 |
HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements |
2022 |
SIGMOD |
7.2428834e-05 |
| 3,489 |
Cosine: A Cloud-Cost Optimized Self-Designing Key-Value Storage Engine |
2022 |
VLDB |
7.2421958e-05 |
| 3,528 |
A Comparative Evaluation of Systems for Scalable Linear Algebra-based Analytics |
2018 |
VLDB |
7.2134232e-05 |
| 3,532 |
Key-Value Storage Engines |
2020 |
SIGMOD |
7.2054521e-05 |
| 3,575 |
Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation |
2021 |
VLDB |
7.1769215e-05 |
| 3,643 |
VISTA: Optimized System for Declarative Feature Transfer from Deep CNNs at Scale |
2020 |
SIGMOD |
7.1227166e-05 |
| 3,679 |
Leaper: A Learned Prefetcher for Cache Invalidation in LSM-tree based Storage Engines |
2020 |
VLDB |
7.0849238e-05 |
| 3,687 |
openGauss: An Autonomous Database System |
2021 |
VLDB |
7.0797286e-05 |
| 3,839 |
Automatic Database Configuration Debugging using Retrieval-Augmented Language Models |
2025 |
SIGMOD |
6.9704205e-05 |
| 3,951 |
Deploying a Steered Query Optimizer in Production at Microsoft |
2022 |
SIGMOD |
6.8884038e-05 |
| 3,959 |
MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems |
2021 |
SIGMOD |
6.8804723e-05 |
| 4,101 |
Towards Dynamic and Safe Configuration Tuning for Cloud Databases |
2022 |
SIGMOD |
6.7930727e-05 |
| 4,343 |
Intelligent Scaling in Amazon Redshift |
2024 |
SIGMOD |
6.6397106e-05 |
| 4,479 |
Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process |
2022 |
SIGMOD |
6.5665703e-05 |
| 4,621 |
The Price of Tailoring the Index to Your Data: Poisoning Attacks on Learned Index Structures |
2022 |
SIGMOD |
6.4828493e-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 |