| 7,238 |
Refactoring Index Tuning Process with Benefit Estimation |
2024 |
VLDB |
5.5624225e-05 |
| 7,257 |
RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems |
2025 |
VLDB |
5.5579707e-05 |
| 7,363 |
Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD |
2024 |
VLDB |
5.5279826e-05 |
| 7,388 |
Towards Foundation Database Models |
2025 |
CIDR |
5.5211011e-05 |
| 7,394 |
ADOPT: Adaptively Optimizing Attribute Orders for Worst-Case Optimal Join Algorithms via Reinforcement Learning |
2023 |
VLDB |
5.5202266e-05 |
| 7,432 |
POLAR: Adaptive and Non-invasive Join Order Selection via Plans of Least Resistance |
2024 |
VLDB |
5.5133928e-05 |
| 7,483 |
T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees |
2025 |
SIGMOD |
5.5007125e-05 |
| 7,561 |
Learned Offline Query Planning via Bayesian Optimization |
2025 |
SIGMOD |
5.4784915e-05 |
| 7,621 |
SageDB: An Instance-Optimized Data Analytics System |
2022 |
VLDB |
5.4664683e-05 |
| 7,997 |
The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions |
2024 |
VLDB |
5.3938336e-05 |
| 8,050 |
NeurDB: On the Design and Implementation of an AI-powered Autonomous Database |
2025 |
CIDR |
5.3839177e-05 |
| 8,064 |
Efficiently Computing Join Orders with Heuristic Search |
2023 |
SIGMOD |
5.3813708e-05 |
| 8,389 |
GenJoin: Conditional Generative Plan-to-Plan Query Optimizer that Learns from Subplan Hints |
2026 |
SIGMOD |
5.3250456e-05 |
| 8,412 |
PARQO: Penalty-Aware Robust Plan Selection in Query Optimization |
2024 |
VLDB |
5.3211467e-05 |
| 8,419 |
The Case for Learned In-Memory Joins |
2023 |
VLDB |
5.3198816e-05 |
| 8,550 |
ROME: Robust Query Optimization via Parallel Multi-Plan Execution |
2024 |
SIGMOD |
5.3030089e-05 |
| 8,657 |
LIMAO: A Framework for Lifelong Modular Learned Query Optimization |
2025 |
VLDB |
5.2790784e-05 |
| 8,790 |
One Size Does Not Fit All: A Bandit-Based Sampler Combination Framework with Theoretical Guarantees |
2022 |
SIGMOD |
5.2633515e-05 |
| 8,872 |
SkinnerMT: Parallelizing for Efficiency and Robustness in Adaptive Query Processing on Multicore Platforms |
2023 |
VLDB |
5.2459616e-05 |
| 8,902 |
Tiresias: Enabling Predictive Autonomous Storage and Indexing |
2022 |
VLDB |
5.2387388e-05 |
| 8,989 |
Conformal Prediction for Verifiable Learned Query Optimization |
2025 |
VLDB |
5.2304457e-05 |
| 8,992 |
GEqO: ML-Accelerated Semantic Equivalence Detection |
2023 |
SIGMOD |
5.2295579e-05 |
| 9,011 |
Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries |
2025 |
VLDB |
5.2238303e-05 |
| 9,041 |
Optimizing the cloud? Don't train models. Build oracles! |
2024 |
CIDR |
5.2183053e-05 |
| 9,141 |
Presto’s History-based Query Optimizer |
2024 |
VLDB |
5.2078543e-05 |
| 9,143 |
Check Out the Big Brain on BRAD: Simplifying Cloud Data Processing with Learned Automated Data Meshes |
2023 |
VLDB |
5.2074327e-05 |
| 9,154 |
Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems |
2024 |
VLDB |
5.2050937e-05 |
| 9,236 |
BASE: Bridging the Gap between Cost and Latency for Query Optimization |
2023 |
VLDB |
5.1882723e-05 |
| 9,385 |
Automatic SQL Error Mitigation in Oracle |
2023 |
VLDB |
5.1697992e-05 |
| 9,583 |
Athena: An Effective Learning-based Framework for Query Optimizer Performance Improvement |
2025 |
SIGMOD |
5.140977e-05 |
| 9,662 |
Low Rank Learning for Offline Query Optimization |
2025 |
SIGMOD |
5.1283524e-05 |
| 9,681 |
Are Joins over LSM-trees Ready? Take RocksDB as an Example |
2025 |
VLDB |
5.1258854e-05 |
| 9,731 |
Database Gyms |
2023 |
CIDR |
5.120066e-05 |
| 9,756 |
APQO: An Adaptive Framework for Parametric Query Optimization |
2026 |
SIGMOD |
5.115551e-05 |
| 9,767 |
PAR2QO: Parametric Penalty-Aware Robust Query Optimization |
2025 |
VLDB |
5.115551e-05 |
| 9,837 |
NeuSO: Neural Optimizer for Subgraph Queries |
2026 |
SIGMOD |
5.1064323e-05 |
| 9,995 |
Graph Transformers for Query Plan Representation: Potentials and Challenges |
2025 |
VLDB |
5.0845476e-05 |
| 10,017 |
The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format |
2024 |
SIGMOD |
5.0825892e-05 |
| 10,074 |
QO-Insight: Inspecting Steered Query Optimizers |
2023 |
VLDB |
5.0732737e-05 |
| 10,109 |
veDB-HTAP: a Highly Integrated, Efficient and Adaptive HTAP System |
2025 |
VLDB |
5.0672857e-05 |
| 10,143 |
Still Asking: How Good Are Query Optimizers, Really? |
2025 |
VLDB |
5.0597449e-05 |
| 10,184 |
Does A Fish Need a Bicycle? The Case for On-Chip NPUs in DBMS |
2026 |
CIDR |
5.052396e-05 |
| 10,206 |
PLATON: Top-down R-tree Packing with Learned Partition Policy |
2023 |
SIGMOD |
5.0491152e-05 |
| 10,249 |
Turbo-Charging SPJ Query Plans with Learned Physical Join Operator Selections |
2022 |
VLDB |
5.0412674e-05 |
| 10,318 |
Towards Full Stack Adaptivity in Permissioned Blockchains |
2024 |
VLDB |
5.0258044e-05 |
| 10,320 |
AdaChain: A Learned Adaptive Blockchain |
2023 |
VLDB |
5.0258044e-05 |
| 10,323 |
This is Going to Sound Crazy, But What If We Used Large Language Models to Boost Automatic Database Tuning Algorithms By Leveraging Prior History? We Will Find Better Configurations More Quickly Than Retraining From Scratch! |
2026 |
SIGMOD |
5.0241309e-05 |
| 10,347 |
Intra-Query Runtime Elasticity for Cloud-Native Data Analysis |
2025 |
SIGMOD |
5.0195882e-05 |
| 10,355 |
SSCard: Substring Cardinality Estimation using Suffix Tree-Guided Learned FM-Index |
2026 |
SIGMOD |
5.0156513e-05 |
| 10,370 |
An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL |
2025 |
SIGMOD |
5.0010514e-05 |