| 142 |
Neo: A Learned Query Optimizer |
2019 |
VLDB |
0.00029114937 |
| 288 |
Graphs-at-a-time: Query Language and Access Methods for Graph Databases |
2008 |
SIGMOD |
0.00022009138 |
| 630 |
DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing |
2025 |
VLDB |
0.00015402076 |
| 646 |
Exploiting Statistics on Query Expressions for Optimization |
2002 |
SIGMOD |
0.00015166402 |
| 787 |
Cosette: An Automated Prover for SQL |
2017 |
CIDR |
0.00013959502 |
| 1,183 |
Simba: Efficient In-Memory Spatial Analytics |
2016 |
SIGMOD |
0.00011589152 |
| 1,261 |
Sampling-Based Query Re-Optimization |
2016 |
SIGMOD |
0.00011289724 |
| 1,282 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00011197535 |
| 1,499 |
SMCQL: Secure Querying for Federated Databases |
2017 |
VLDB |
0.00010445281 |
| 1,505 |
Keyword Search in Databases: The Power of RDBMS |
2009 |
SIGMOD |
0.00010424285 |
| 1,754 |
Combining Histograms and Parametric Curve Fitting for Feedback-Driven Query Result-Size Estimation |
1999 |
VLDB |
9.7111856e-05 |
| 1,821 |
Joins via Geometric Resolutions: Worst-case and Beyond |
2015 |
PODS |
9.5466386e-05 |
| 2,011 |
Pregelix: Big(ger) Graph Analytics on A Dataflow Engine |
2015 |
VLDB |
9.1800407e-05 |
| 2,167 |
DIFF: A Relational Interface for Large-Scale Data Explanation |
2019 |
VLDB |
8.9166414e-05 |
| 2,290 |
Active Learning for ML Enhanced Database Systems |
2020 |
SIGMOD |
8.6813363e-05 |
| 2,407 |
Declarative Recursive Computation on an RDBMS or, Why You Should Use a Database For Distributed Machine Learning |
2019 |
VLDB |
8.4928721e-05 |
| 2,888 |
Query Optimizers: Time to Rethink the Contract? |
2009 |
SIGMOD |
7.8895201e-05 |
| 3,138 |
How to Win a Hot Dog Eating Contest: Distributed Incremental View Maintenance with Batch Updates |
2016 |
SIGMOD |
7.5866991e-05 |
| 3,489 |
Cosine: A Cloud-Cost Optimized Self-Designing Key-Value Storage Engine |
2022 |
VLDB |
7.2421958e-05 |
| 3,513 |
Serving and Optimizing Machine Learning Workflows on Heterogeneous Infrastructures |
2023 |
VLDB |
7.2253231e-05 |
| 3,606 |
Access Path Selection in Main-Memory Optimized Data Systems: Should I Scan or Should I Probe? |
2017 |
SIGMOD |
7.1528863e-05 |
| 4,459 |
Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts |
2022 |
SIGMOD |
6.5757572e-05 |
| 4,583 |
QUEST: Query Optimization in Unstructured Document Analysis |
2025 |
VLDB |
6.5079225e-05 |
| 5,029 |
COMPASS: Online Sketch-based Query Optimization for In-Memory Databases |
2021 |
SIGMOD |
6.2952031e-05 |
| 5,044 |
Analyzing the Impact of Cardinality Estimation on Execution Plans in Microsoft SQL Server |
2023 |
VLDB |
6.2888728e-05 |
| 5,056 |
Lightweight Cardinality Estimation in LSM-based Systems |
2018 |
SIGMOD |
6.282339e-05 |
| 5,245 |
FASTgres: Making Learned Query Optimizer Hinting Effective |
2023 |
VLDB |
6.1995935e-05 |
| 5,484 |
A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies |
2024 |
VLDB |
6.0980944e-05 |
| 5,598 |
Efficient Computation of Multiple Group By Queries |
2005 |
SIGMOD |
6.053914e-05 |
| 5,673 |
Enabling Incremental Query Re-Optimization |
2016 |
SIGMOD |
6.0252485e-05 |
| 6,051 |
Size and Treewidth Bounds for Conjunctive Queries |
2009 |
PODS |
5.8865476e-05 |
| 6,243 |
Operator and Query Progress Estimation in Microsoft SQL Server Live Query Statistics |
2016 |
SIGMOD |
5.8220831e-05 |
| 6,315 |
Memory-Aware Framework for Efficient Second-Order Random Walk on Large Graphs |
2020 |
SIGMOD |
5.7968933e-05 |
| 6,584 |
Can Large Language Models Be Query Optimizer for Relational Databases? |
2026 |
SIGMOD |
5.72395e-05 |
| 6,615 |
Multi-Objective Agentic Rewrites for Unstructured Data Processing |
2026 |
VLDB |
5.7164252e-05 |
| 6,684 |
Query Optimization over Crowdsourced Data |
2013 |
VLDB |
5.6940605e-05 |
| 6,768 |
Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities |
2022 |
SIGMOD |
5.6693759e-05 |
| 7,487 |
Membrane - Safe and Performant Data Access Controls in Apache Spark in the Presence of Imperative Code |
2024 |
VLDB |
5.4995746e-05 |
| 7,587 |
Convolution and Cross-Correlation of Count Sketches Enables Fast Cardinality Estimation of Multi-Join Queries |
2024 |
SIGMOD |
5.4745198e-05 |
| 7,653 |
MRTuner: A Toolkit to Enable Holistic Optimization for MapReduce Jobs |
2014 |
VLDB |
5.4592529e-05 |
| 7,941 |
SlabCity: Whole-Query Optimization using Program Synthesis |
2023 |
VLDB |
5.4056478e-05 |
| 7,975 |
Robust Query Processing: Mission Possible |
2020 |
VLDB |
5.3985544e-05 |
| 7,976 |
Distributed Outlier Detection using Compressive Sensing |
2015 |
SIGMOD |
5.3981912e-05 |
| 8,012 |
From a Stream of Relational Queries to Distributed Stream Processing |
2010 |
VLDB |
5.3911783e-05 |
| 8,023 |
Processing and Optimizing Main Memory Spatial-Keyword Queries |
2016 |
VLDB |
5.3888101e-05 |
| 8,188 |
Efficient Query Re-optimization with Judicious Subquery Selections |
2023 |
SIGMOD |
5.3649397e-05 |
| 8,286 |
User-Optimizer Communication using Abstract Plans in Sybase ASE |
2001 |
VLDB |
5.3449621e-05 |
| 8,361 |
MONSOON: Multi-Step Optimization and Execution of Queries with Partially Obscured Predicates |
2020 |
SIGMOD |
5.3310744e-05 |
| 8,388 |
List Intersection for Web Search: Algorithms, Cost Models, and Optimizations |
2019 |
VLDB |
5.3257622e-05 |
| 8,539 |
New Query Optimization Techniques in the Spark Engine of Azure Synapse |
2022 |
VLDB |
5.3048225e-05 |