| 154 |
Neo: A Learned Query Optimizer |
2019 |
VLDB |
0.00028726181 |
| 294 |
Graphs-at-a-time: Query Language and Access Methods for Graph Databases |
2008 |
SIGMOD |
0.00022253507 |
| 664 |
Exploiting Statistics on Query Expressions for Optimization |
2002 |
SIGMOD |
0.00015167825 |
| 910 |
Cosette: An Automated Prover for SQL |
2017 |
CIDR |
0.00013285905 |
| 1,175 |
Simba: Efficient In-Memory Spatial Analytics |
2016 |
SIGMOD |
0.00011812263 |
| 1,256 |
Sampling-Based Query Re-Optimization |
2016 |
SIGMOD |
0.00011457194 |
| 1,279 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00011361878 |
| 1,343 |
DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing |
2025 |
VLDB |
0.00011095866 |
| 1,459 |
SMCQL: Secure Querying for Federated Databases |
2017 |
VLDB |
0.00010717725 |
| 1,555 |
Keyword Search in Databases: The Power of RDBMS |
2009 |
SIGMOD |
0.00010370683 |
| 1,729 |
Combining Histograms and Parametric Curve Fitting for Feedback-Driven Query Result-Size Estimation |
1999 |
VLDB |
9.908788e-05 |
| 1,857 |
Joins via Geometric Resolutions: Worst-case and Beyond |
2015 |
PODS |
9.6047945e-05 |
| 1,983 |
Pregelix: Big(ger) Graph Analytics on A Dataflow Engine |
2015 |
VLDB |
9.3544951e-05 |
| 2,161 |
DIFF: A Relational Interface for Large-Scale Data Explanation |
2019 |
VLDB |
9.0606664e-05 |
| 2,313 |
Active Learning for ML Enhanced Database Systems |
2020 |
SIGMOD |
8.762627e-05 |
| 2,370 |
Declarative Recursive Computation on an RDBMS or, Why You Should Use a Database For Distributed Machine Learning |
2019 |
VLDB |
8.6795925e-05 |
| 2,944 |
Query Optimizers: Time to Rethink the Contract? |
2009 |
SIGMOD |
7.9335187e-05 |
| 3,087 |
How to Win a Hot Dog Eating Contest: Distributed Incremental View Maintenance with Batch Updates |
2016 |
SIGMOD |
7.7702906e-05 |
| 3,577 |
Cosine: A Cloud-Cost Optimized Self-Designing Key-Value Storage Engine |
2022 |
VLDB |
7.2930211e-05 |
| 3,598 |
Access Path Selection in Main-Memory Optimized Data Systems: Should I Scan or Should I Probe? |
2017 |
SIGMOD |
7.2718988e-05 |
| 4,436 |
Serving and Optimizing Machine Learning Workflows on Heterogeneous Infrastructures |
2023 |
VLDB |
6.7069035e-05 |
| 4,612 |
Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts |
2022 |
SIGMOD |
6.6072026e-05 |
| 4,900 |
COMPASS: Online Sketch-based Query Optimization for In-Memory Databases |
2021 |
SIGMOD |
6.4534715e-05 |
| 4,945 |
Lightweight Cardinality Estimation in LSM-based Systems |
2018 |
SIGMOD |
6.4321265e-05 |
| 5,010 |
Analyzing the Impact of Cardinality Estimation on Execution Plans in Microsoft SQL Server |
2023 |
VLDB |
6.4023732e-05 |
| 5,277 |
FASTgres: Making Learned Query Optimizer Hinting Effective |
2023 |
VLDB |
6.2859099e-05 |
| 5,470 |
Efficient Computation of Multiple Group By Queries |
2005 |
SIGMOD |
6.2070458e-05 |
| 5,552 |
Enabling Incremental Query Re-Optimization |
2016 |
SIGMOD |
6.1778488e-05 |
| 5,767 |
A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies |
2024 |
VLDB |
6.0945741e-05 |
| 5,982 |
Size and Treewidth Bounds for Conjunctive Queries |
2009 |
PODS |
6.0207284e-05 |
| 6,138 |
Operator and Query Progress Estimation in Microsoft SQL Server Live Query Statistics |
2016 |
SIGMOD |
5.9640712e-05 |
| 6,371 |
QUEST: Query Optimization in Unstructured Document Analysis |
2025 |
VLDB |
5.8962187e-05 |
| 6,423 |
Memory-Aware Framework for Efficient Second-Order Random Walk on Large Graphs |
2020 |
SIGMOD |
5.8813146e-05 |
| 6,548 |
Query Optimization over Crowdsourced Data |
2013 |
VLDB |
5.8443704e-05 |
| 6,939 |
Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities |
2022 |
SIGMOD |
5.7338637e-05 |
| 7,401 |
Membrane - Safe and Performant Data Access Controls in Apache Spark in the Presence of Imperative Code |
2024 |
VLDB |
5.6255291e-05 |
| 7,546 |
MRTuner: A Toolkit to Enable Holistic Optimization for MapReduce Jobs |
2014 |
VLDB |
5.6024593e-05 |
| 7,747 |
Convolution and Cross-Correlation of Count Sketches Enables Fast Cardinality Estimation of Multi-Join Queries |
2024 |
SIGMOD |
5.5529458e-05 |
| 7,795 |
Distributed Outlier Detection using Compressive Sensing |
2015 |
SIGMOD |
5.5429229e-05 |
| 7,809 |
Can Large Language Models Be Query Optimizer for Relational Databases? |
2026 |
SIGMOD |
5.5399022e-05 |
| 7,829 |
Robust Query Processing: Mission Possible |
2020 |
VLDB |
5.5360082e-05 |
| 7,840 |
From a Stream of Relational Queries to Distributed Stream Processing |
2010 |
VLDB |
5.5339505e-05 |
| 7,842 |
Processing and Optimizing Main Memory Spatial-Keyword Queries |
2016 |
VLDB |
5.5333985e-05 |
| 8,119 |
User-Optimizer Communication using Abstract Plans in Sybase ASE |
2001 |
VLDB |
5.4835315e-05 |
| 8,164 |
SlabCity: Whole-Query Optimization using Program Synthesis |
2023 |
VLDB |
5.4750309e-05 |
| 8,201 |
List Intersection for Web Search: Algorithms, Cost Models, and Optimizations |
2019 |
VLDB |
5.467444e-05 |
| 8,211 |
MONSOON: Multi-Step Optimization and Execution of Queries with Partially Obscured Predicates |
2020 |
SIGMOD |
5.4658735e-05 |
| 8,439 |
New Query Optimization Techniques in the Spark Engine of Azure Synapse |
2022 |
VLDB |
5.4248071e-05 |
| 8,678 |
Building Statistical Models and Scoring with UDFs |
2007 |
SIGMOD |
5.3864318e-05 |
| 8,783 |
Tiresias: Enabling Predictive Autonomous Storage and Indexing |
2022 |
VLDB |
5.3740362e-05 |