| 145 |
Neo: A Learned Query Optimizer |
2019 |
VLDB |
0.0002908188 |
| 288 |
Graphs-at-a-time: Query Language and Access Methods for Graph Databases |
2008 |
SIGMOD |
0.00021969641 |
| 646 |
Exploiting Statistics on Query Expressions for Optimization |
2002 |
SIGMOD |
0.0001520859 |
| 683 |
DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing |
2025 |
VLDB |
0.00014817539 |
| 790 |
Cosette: An Automated Prover for SQL |
2017 |
CIDR |
0.00013976438 |
| 1,178 |
Simba: Efficient In-Memory Spatial Analytics |
2016 |
SIGMOD |
0.00011632691 |
| 1,257 |
Sampling-Based Query Re-Optimization |
2016 |
SIGMOD |
0.00011310561 |
| 1,279 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00011226878 |
| 1,495 |
SMCQL: Secure Querying for Federated Databases |
2017 |
VLDB |
0.00010484897 |
| 1,501 |
Keyword Search in Databases: The Power of RDBMS |
2009 |
SIGMOD |
0.00010461358 |
| 1,741 |
Combining Histograms and Parametric Curve Fitting for Feedback-Driven Query Result-Size Estimation |
1999 |
VLDB |
9.7382372e-05 |
| 1,812 |
Joins via Geometric Resolutions: Worst-case and Beyond |
2015 |
PODS |
9.5803973e-05 |
| 1,998 |
Pregelix: Big(ger) Graph Analytics on A Dataflow Engine |
2015 |
VLDB |
9.2144238e-05 |
| 2,160 |
DIFF: A Relational Interface for Large-Scale Data Explanation |
2019 |
VLDB |
8.9364035e-05 |
| 2,275 |
Active Learning for ML Enhanced Database Systems |
2020 |
SIGMOD |
8.7090584e-05 |
| 2,400 |
Declarative Recursive Computation on an RDBMS or, Why You Should Use a Database For Distributed Machine Learning |
2019 |
VLDB |
8.5213814e-05 |
| 2,891 |
Query Optimizers: Time to Rethink the Contract? |
2009 |
SIGMOD |
7.9021718e-05 |
| 3,128 |
How to Win a Hot Dog Eating Contest: Distributed Incremental View Maintenance with Batch Updates |
2016 |
SIGMOD |
7.6151967e-05 |
| 3,479 |
Cosine: A Cloud-Cost Optimized Self-Designing Key-Value Storage Engine |
2022 |
VLDB |
7.2695068e-05 |
| 3,508 |
Serving and Optimizing Machine Learning Workflows on Heterogeneous Infrastructures |
2023 |
VLDB |
7.2490197e-05 |
| 3,599 |
Access Path Selection in Main-Memory Optimized Data Systems: Should I Scan or Should I Probe? |
2017 |
SIGMOD |
7.1773938e-05 |
| 4,563 |
Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts |
2022 |
SIGMOD |
6.5320994e-05 |
| 4,731 |
QUEST: Query Optimization in Unstructured Document Analysis |
2025 |
VLDB |
6.4462032e-05 |
| 5,003 |
COMPASS: Online Sketch-based Query Optimization for In-Memory Databases |
2021 |
SIGMOD |
6.3188773e-05 |
| 5,022 |
Analyzing the Impact of Cardinality Estimation on Execution Plans in Microsoft SQL Server |
2023 |
VLDB |
6.3100988e-05 |
| 5,044 |
Lightweight Cardinality Estimation in LSM-based Systems |
2018 |
SIGMOD |
6.30014e-05 |
| 5,241 |
FASTgres: Making Learned Query Optimizer Hinting Effective |
2023 |
VLDB |
6.2154384e-05 |
| 5,481 |
A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies |
2024 |
VLDB |
6.1125124e-05 |
| 5,582 |
Efficient Computation of Multiple Group By Queries |
2005 |
SIGMOD |
6.0768264e-05 |
| 5,667 |
Enabling Incremental Query Re-Optimization |
2016 |
SIGMOD |
6.0458446e-05 |
| 6,043 |
Size and Treewidth Bounds for Conjunctive Queries |
2009 |
PODS |
5.9060629e-05 |
| 6,241 |
Operator and Query Progress Estimation in Microsoft SQL Server Live Query Statistics |
2016 |
SIGMOD |
5.8381762e-05 |
| 6,301 |
Memory-Aware Framework for Efficient Second-Order Random Walk on Large Graphs |
2020 |
SIGMOD |
5.8188746e-05 |
| 6,586 |
Can Large Language Models Be Query Optimizer for Relational Databases? |
2026 |
SIGMOD |
5.7430662e-05 |
| 6,668 |
Query Optimization over Crowdsourced Data |
2013 |
VLDB |
5.7147473e-05 |
| 6,753 |
Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities |
2022 |
SIGMOD |
5.6904085e-05 |
| 6,886 |
Multi-Objective Agentic Rewrites for Unstructured Data Processing |
2026 |
VLDB |
5.6551172e-05 |
| 7,464 |
Membrane - Safe and Performant Data Access Controls in Apache Spark in the Presence of Imperative Code |
2024 |
VLDB |
5.5204333e-05 |
| 7,566 |
Convolution and Cross-Correlation of Count Sketches Enables Fast Cardinality Estimation of Multi-Join Queries |
2024 |
SIGMOD |
5.4952834e-05 |
| 7,632 |
MRTuner: A Toolkit to Enable Holistic Optimization for MapReduce Jobs |
2014 |
VLDB |
5.4793438e-05 |
| 7,931 |
SlabCity: Whole-Query Optimization using Program Synthesis |
2023 |
VLDB |
5.4238328e-05 |
| 7,954 |
Robust Query Processing: Mission Possible |
2020 |
VLDB |
5.4190023e-05 |
| 7,955 |
Distributed Outlier Detection using Compressive Sensing |
2015 |
SIGMOD |
5.4185826e-05 |
| 7,990 |
From a Stream of Relational Queries to Distributed Stream Processing |
2010 |
VLDB |
5.4116144e-05 |
| 8,001 |
Processing and Optimizing Main Memory Spatial-Keyword Queries |
2016 |
VLDB |
5.4092483e-05 |
| 8,164 |
Efficient Query Re-optimization with Judicious Subquery Selections |
2023 |
SIGMOD |
5.3852872e-05 |
| 8,290 |
User-Optimizer Communication using Abstract Plans in Sybase ASE |
2001 |
VLDB |
5.3614554e-05 |
| 8,345 |
MONSOON: Multi-Step Optimization and Execution of Queries with Partially Obscured Predicates |
2020 |
SIGMOD |
5.3511996e-05 |
| 8,368 |
List Intersection for Web Search: Algorithms, Cost Models, and Optimizations |
2019 |
VLDB |
5.3459616e-05 |
| 8,535 |
New Query Optimization Techniques in the Spark Engine of Azure Synapse |
2022 |
VLDB |
5.320973e-05 |