| 329 |
Neo: A Learned Query Optimizer |
2019 |
VLDB |
0.00027301488 |
| 634 |
Bao: Making Learned Query Optimization Practical |
2021 |
SIGMOD |
0.00018844568 |
| 876 |
Plan-Structured Deep Neural Network Models for Query Performance Prediction |
2019 |
VLDB |
0.00015660534 |
| 1,438 |
Benchmarking Learned Indexes |
2021 |
VLDB |
0.00011965956 |
| 1,462 |
ARDA: Automatic Relational Data Augmentation for Machine Learning |
2020 |
VLDB |
0.00011866333 |
| 1,856 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00010319105 |
| 2,781 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
8.1282042e-05 |
| 3,222 |
WiSeDB: A Learning-based Workload Management Advisor for Cloud Databases |
2016 |
VLDB |
7.3531422e-05 |
| 3,658 |
Towards a Hands-Free Query Optimizer through Deep Learning |
2019 |
CIDR |
6.8700949e-05 |
| 4,069 |
CDFShop: Exploring and Optimizing Learned Index Structures |
2020 |
SIGMOD |
6.4744708e-05 |
| 4,413 |
Robust Query Driven Cardinality Estimation under Changing Workloads |
2023 |
VLDB |
6.1989918e-05 |
| 4,592 |
Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift |
2023 |
SIGMOD |
6.056004e-05 |
| 4,966 |
Releasing Cloud Databases from the Chains of Performance Prediction Models |
2017 |
CIDR |
5.7949047e-05 |
| 5,412 |
Kepler: Robust Learning for Faster Parametric Query Optimization |
2023 |
SIGMOD |
5.5200608e-05 |
| 5,443 |
NashDB: An End-to-End Economic Method for Elastic Database Fragmentation, Replication, and Provisioning |
2018 |
SIGMOD |
5.5020716e-05 |
| 5,654 |
AutoSteer: Learned Query Optimization for Any SQL Database |
2023 |
VLDB |
5.3882121e-05 |
| 5,844 |
Stage: Query Execution Time Prediction in Amazon Redshift |
2024 |
SIGMOD |
5.3060581e-05 |
| 5,994 |
Steering Query Optimizers: A Practical Take on Big Data Workloads |
2021 |
SIGMOD |
5.2367998e-05 |
| 8,434 |
SageDB: An Instance-Optimized Data Analytics System |
2022 |
VLDB |
4.5077955e-05 |
| 8,660 |
Learned Offline Query Planning via Bayesian Optimization |
2025 |
SIGMOD |
4.4680058e-05 |
| 9,581 |
Low Rank Learning for Offline Query Optimization |
2025 |
SIGMOD |
4.3186744e-05 |
| 9,709 |
QO-Insight: Inspecting Steered Query Optimizers |
2023 |
VLDB |
4.2951473e-05 |
| 9,811 |
A Practical Theory of Generalization in Selectivity Learning |
2025 |
VLDB |
4.2742278e-05 |
| 9,980 |
Survivorship Bias in Industrial Database Workloads |
2026 |
CIDR |
4.1905499e-05 |
| 10,045 |
Adaptive Sharding in Untrusted Environments |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,112 |
SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,307 |
Global Hash Tables Strike Back! An Analysis of Parallel GROUP BY Aggregation |
2026 |
VLDB |
4.1905499e-05 |
| 10,462 |
ScaleLLM: A Technique for Scalable LLM-augmented Data Systems |
2025 |
SIGMOD |
4.1905499e-05 |
| 10,627 |
Data-Agnostic Cardinality Learning from Imperfect Workloads |
2025 |
VLDB |
4.1905499e-05 |
| 11,002 |
Towards Full Stack Adaptivity in Permissioned Blockchains |
2024 |
VLDB |
4.1905499e-05 |
| 11,238 |
AdaChain: A Learned Adaptive Blockchain |
2023 |
VLDB |
4.1905499e-05 |
| 11,682 |
NashDB: Fragmentation, Replication, and Provisioning using Economic Methods |
2019 |
VLDB |
4.1905499e-05 |
| 13,174 |
BFTGym: An Interactive Playground for BFT Protocols |
2024 |
VLDB |
- |