| 144 |
Neo: A Learned Query Optimizer |
2019 |
VLDB |
0.00029090793 |
| 289 |
Graphs-at-a-time: Query Language and Access Methods for Graph Databases |
2008 |
SIGMOD |
0.00021960834 |
| 644 |
Exploiting Statistics on Query Expressions for Optimization |
2002 |
SIGMOD |
0.00015209065 |
| 658 |
DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing |
2025 |
VLDB |
0.00015058738 |
| 790 |
Cosette: An Automated Prover for SQL |
2017 |
CIDR |
0.00013971102 |
| 1,178 |
Simba: Efficient In-Memory Spatial Analytics |
2016 |
SIGMOD |
0.00011627256 |
| 1,258 |
Sampling-Based Query Re-Optimization |
2016 |
SIGMOD |
0.00011308863 |
| 1,280 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00011224914 |
| 1,496 |
SMCQL: Secure Querying for Federated Databases |
2017 |
VLDB |
0.00010479934 |
| 1,501 |
Keyword Search in Databases: The Power of RDBMS |
2009 |
SIGMOD |
0.00010456517 |
| 1,743 |
Combining Histograms and Parametric Curve Fitting for Feedback-Driven Query Result-Size Estimation |
1999 |
VLDB |
9.7342409e-05 |
| 1,813 |
Joins via Geometric Resolutions: Worst-case and Beyond |
2015 |
PODS |
9.5759542e-05 |
| 2,000 |
Pregelix: Big(ger) Graph Analytics on A Dataflow Engine |
2015 |
VLDB |
9.2101691e-05 |
| 2,162 |
DIFF: A Relational Interface for Large-Scale Data Explanation |
2019 |
VLDB |
8.9344773e-05 |
| 2,278 |
Active Learning for ML Enhanced Database Systems |
2020 |
SIGMOD |
8.7057608e-05 |
| 2,401 |
Declarative Recursive Computation on an RDBMS or, Why You Should Use a Database For Distributed Machine Learning |
2019 |
VLDB |
8.517457e-05 |
| 2,890 |
Query Optimizers: Time to Rethink the Contract? |
2009 |
SIGMOD |
7.9010819e-05 |
| 3,128 |
How to Win a Hot Dog Eating Contest: Distributed Incremental View Maintenance with Batch Updates |
2016 |
SIGMOD |
7.611678e-05 |
| 3,480 |
Cosine: A Cloud-Cost Optimized Self-Designing Key-Value Storage Engine |
2022 |
VLDB |
7.2661848e-05 |
| 3,508 |
Serving and Optimizing Machine Learning Workflows on Heterogeneous Infrastructures |
2023 |
VLDB |
7.2455881e-05 |
| 3,597 |
Access Path Selection in Main-Memory Optimized Data Systems: Should I Scan or Should I Probe? |
2017 |
SIGMOD |
7.1759026e-05 |
| 4,559 |
Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts |
2022 |
SIGMOD |
6.5324275e-05 |
| 4,565 |
QUEST: Query Optimization in Unstructured Document Analysis |
2025 |
VLDB |
6.5295131e-05 |
| 5,006 |
COMPASS: Online Sketch-based Query Optimization for In-Memory Databases |
2021 |
SIGMOD |
6.3159614e-05 |
| 5,020 |
Analyzing the Impact of Cardinality Estimation on Execution Plans in Microsoft SQL Server |
2023 |
VLDB |
6.3096708e-05 |
| 5,047 |
Lightweight Cardinality Estimation in LSM-based Systems |
2018 |
SIGMOD |
6.2972183e-05 |
| 5,236 |
FASTgres: Making Learned Query Optimizer Hinting Effective |
2023 |
VLDB |
6.2153504e-05 |
| 5,482 |
A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies |
2024 |
VLDB |
6.1123461e-05 |
| 5,583 |
Efficient Computation of Multiple Group By Queries |
2005 |
SIGMOD |
6.0739524e-05 |
| 5,663 |
Enabling Incremental Query Re-Optimization |
2016 |
SIGMOD |
6.0448133e-05 |
| 6,044 |
Size and Treewidth Bounds for Conjunctive Queries |
2009 |
PODS |
5.903331e-05 |
| 6,243 |
Operator and Query Progress Estimation in Microsoft SQL Server Live Query Statistics |
2016 |
SIGMOD |
5.8357659e-05 |
| 6,305 |
Memory-Aware Framework for Efficient Second-Order Random Walk on Large Graphs |
2020 |
SIGMOD |
5.8161222e-05 |
| 6,575 |
Can Large Language Models Be Query Optimizer for Relational Databases? |
2026 |
SIGMOD |
5.7428777e-05 |
| 6,607 |
Multi-Objective Agentic Rewrites for Unstructured Data Processing |
2026 |
VLDB |
5.73539e-05 |
| 6,672 |
Query Optimization over Crowdsourced Data |
2013 |
VLDB |
5.7120461e-05 |
| 6,758 |
Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities |
2022 |
SIGMOD |
5.6877154e-05 |
| 7,468 |
Membrane - Safe and Performant Data Access Controls in Apache Spark in the Presence of Imperative Code |
2024 |
VLDB |
5.51782e-05 |
| 7,572 |
Convolution and Cross-Correlation of Count Sketches Enables Fast Cardinality Estimation of Multi-Join Queries |
2024 |
SIGMOD |
5.492682e-05 |
| 7,638 |
MRTuner: A Toolkit to Enable Holistic Optimization for MapReduce Jobs |
2014 |
VLDB |
5.4767699e-05 |
| 7,929 |
SlabCity: Whole-Query Optimization using Program Synthesis |
2023 |
VLDB |
5.4231855e-05 |
| 7,958 |
Robust Query Processing: Mission Possible |
2020 |
VLDB |
5.4164639e-05 |
| 7,959 |
Distributed Outlier Detection using Compressive Sensing |
2015 |
SIGMOD |
5.4160954e-05 |
| 7,995 |
From a Stream of Relational Queries to Distributed Stream Processing |
2010 |
VLDB |
5.4090565e-05 |
| 8,006 |
Processing and Optimizing Main Memory Spatial-Keyword Queries |
2016 |
VLDB |
5.4066876e-05 |
| 8,170 |
Efficient Query Re-optimization with Judicious Subquery Selections |
2023 |
SIGMOD |
5.3827384e-05 |
| 8,296 |
User-Optimizer Communication using Abstract Plans in Sybase ASE |
2001 |
VLDB |
5.3589207e-05 |
| 8,348 |
MONSOON: Multi-Step Optimization and Execution of Queries with Partially Obscured Predicates |
2020 |
SIGMOD |
5.3486679e-05 |
| 8,372 |
List Intersection for Web Search: Algorithms, Cost Models, and Optimizations |
2019 |
VLDB |
5.3434309e-05 |
| 8,542 |
New Query Optimization Techniques in the Spark Engine of Azure Synapse |
2022 |
VLDB |
5.3188219e-05 |