| 85 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00035864347 |
| 314 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.00021282642 |
| 437 |
QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning |
2019 |
VLDB |
0.00018315867 |
| 555 |
SageDB: A Learned Database System |
2019 |
CIDR |
0.00016506678 |
| 1,132 |
Qd-tree: Learning Data Layouts for Big Data Analytics |
2020 |
SIGMOD |
0.00011898257 |
| 1,156 |
QuickSel: Quick Selectivity Learning with Mixture Models |
2020 |
SIGMOD |
0.00011777105 |
| 1,250 |
DB-BERT: A Database Tuning Tool that "Reads the Manual" |
2022 |
SIGMOD |
0.00011339256 |
| 1,279 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00011226878 |
| 1,289 |
An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems |
2021 |
VLDB |
0.00011162479 |
| 1,433 |
Towards a Learning Optimizer for Shared Clouds |
2019 |
VLDB |
0.00010677711 |
| 1,513 |
Cloud-Native Database Systems at Alibaba: Opportunities and Challenges |
2019 |
VLDB |
0.00010429438 |
| 1,550 |
Updatable Learned Index with Precise Positions |
2021 |
VLDB |
0.00010282449 |
| 1,605 |
The Data Calculator*: Data Structure Design and Cost Synthesis from First Principles and Learned Cost Models |
2018 |
SIGMOD |
0.00010093796 |
| 1,699 |
Black or White? How to Develop an AutoTuner for Memory-based Analytics |
2020 |
SIGMOD |
9.8445322e-05 |
| 1,857 |
Diagnosing Root Causes of Intermittent Slow Queries in Cloud Databases |
2020 |
VLDB |
9.4929201e-05 |
| 1,889 |
Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn |
2019 |
CIDR |
9.4273689e-05 |
| 2,004 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
9.2065719e-05 |
| 2,231 |
GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization |
2024 |
VLDB |
8.7982985e-05 |
| 2,275 |
Active Learning for ML Enhanced Database Systems |
2020 |
SIGMOD |
8.7090584e-05 |
| 2,583 |
Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation |
2021 |
VLDB |
8.2589758e-05 |
| 2,720 |
ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases |
2021 |
SIGMOD |
8.0966919e-05 |
| 2,765 |
Instance-Optimized Data Layouts for Cloud Analytics Workloads |
2021 |
SIGMOD |
8.0439015e-05 |
| 2,772 |
Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation |
2022 |
VLDB |
8.035288e-05 |
| 2,882 |
Optimal Column Layout for Hybrid Workloads |
2019 |
VLDB |
7.9116043e-05 |
| 2,908 |
AI Meets Database: AI4DB and DB4AI |
2021 |
SIGMOD |
7.8742664e-05 |
| 3,028 |
Autoscaling Tiered Cloud Storage in Anna |
2019 |
VLDB |
7.7377953e-05 |
| 3,032 |
iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases |
2019 |
VLDB |
7.7351139e-05 |
| 3,051 |
LlamaTune: Sample-Efficient DBMS Configuration Tuning |
2022 |
VLDB |
7.7055931e-05 |
| 3,158 |
CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions |
2021 |
VLDB |
7.5811757e-05 |
| 3,169 |
Panda: Performance Debugging for Databases using LLM Agents |
2024 |
CIDR |
7.5696238e-05 |
| 3,406 |
Native Store Extension for SAP HANA |
2019 |
VLDB |
7.3281944e-05 |
| 3,430 |
A Demonstration of the OtterTune Automatic Database Management System Tuning Service |
2018 |
VLDB |
7.3056632e-05 |
| 3,479 |
Cosine: A Cloud-Cost Optimized Self-Designing Key-Value Storage Engine |
2022 |
VLDB |
7.2695068e-05 |
| 3,486 |
HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements |
2022 |
SIGMOD |
7.2636102e-05 |
| 3,518 |
A Comparative Evaluation of Systems for Scalable Linear Algebra-based Analytics |
2018 |
VLDB |
7.2400627e-05 |
| 3,525 |
Key-Value Storage Engines |
2020 |
SIGMOD |
7.2327042e-05 |
| 3,563 |
Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift |
2023 |
SIGMOD |
7.2042148e-05 |
| 3,590 |
Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation |
2021 |
VLDB |
7.1865343e-05 |
| 3,630 |
VISTA: Optimized System for Declarative Feature Transfer from Deep CNNs at Scale |
2020 |
SIGMOD |
7.1496182e-05 |
| 3,671 |
Leaper: A Learned Prefetcher for Cache Invalidation in LSM-tree based Storage Engines |
2020 |
VLDB |
7.1100217e-05 |
| 3,682 |
openGauss: An Autonomous Database System |
2021 |
VLDB |
7.1013922e-05 |
| 3,949 |
Deploying a Steered Query Optimizer in Production at Microsoft |
2022 |
SIGMOD |
6.9052796e-05 |
| 3,965 |
MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems |
2021 |
SIGMOD |
6.8918628e-05 |
| 4,079 |
Towards Dynamic and Safe Configuration Tuning for Cloud Databases |
2022 |
SIGMOD |
6.818264e-05 |
| 4,114 |
Automatic Database Configuration Debugging using Retrieval-Augmented Language Models |
2025 |
SIGMOD |
6.7971182e-05 |
| 4,457 |
Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process |
2022 |
SIGMOD |
6.5913732e-05 |
| 4,616 |
The Price of Tailoring the Index to Your Data: Poisoning Attacks on Learned Index Structures |
2022 |
SIGMOD |
6.5000712e-05 |
| 4,666 |
Intelligent Scaling in Amazon Redshift |
2024 |
SIGMOD |
6.479878e-05 |
| 4,741 |
Machine Learning for Databases |
2021 |
VLDB |
6.4410027e-05 |
| 4,781 |
Learned Approximate Query Processing: Make it Light, Accurate and Fast |
2021 |
CIDR |
6.4162085e-05 |