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NeuroCard: One Cardinality Estimator for All Tables

Summary: NeuroCard uses a single neural density estimator over the database to model join cardinalities, with no independence assumptions. Join sampling and autoregressive modeling achieve state-of-the-art accuracy; scalable to dozens of tables and compact to train. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12579
Venue
VLDB
Year
2021
Pagerank
0.00015423056
Overall Rank
910 | 93.68%
DOI
10.14778/3421424.3421432

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 50 of 90 citing papers.

Rank Citing Paper Year Venue Pagerank
640 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00018759152
1,638 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00011049779
1,703 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00010836769
2,121 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 9.5017232e-05
2,762 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 8.1585394e-05
2,783 Flow-Loss: Learning Cardinality Estimates That Matter 2021 VLDB 8.1293383e-05
2,985 DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems 2021 VLDB 7.7795847e-05
3,001 Neural Subgraph Counting with Wasserstein Estimator 2022 SIGMOD 7.7404487e-05
3,266 Learned Cardinality Estimation: An In-depth Study 2022 SIGMOD 7.3074684e-05
3,348 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB 7.1904529e-05
3,449 Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation 2022 VLDB 7.0824319e-05
3,499 Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation 2021 VLDB 7.0376445e-05
3,727 Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection 2022 VLDB 6.8141709e-05
3,779 Instance-Optimized Data Layouts for Cloud Analytics Workloads 2021 SIGMOD 6.7747205e-05
3,828 Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction 2022 VLDB 6.7208524e-05
3,924 A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation 2021 SIGMOD 6.6271553e-05
3,990 FactorJoin: A New Cardinality Estimation Framework for Join Queries 2023 SIGMOD 6.5581983e-05
4,152 openGauss: An Autonomous Database System 2021 VLDB 6.4060406e-05
4,417 Robust Query Driven Cardinality Estimation under Changing Workloads 2023 VLDB 6.2037371e-05
4,434 Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process 2022 SIGMOD 6.1929999e-05
4,543 FACE: A Normalizing Flow based Cardinality Estimator 2022 VLDB 6.1011198e-05
4,661 PreQR: Pre-training Representation for SQL Understanding 2022 SIGMOD 6.0137947e-05
4,842 Towards Dynamic and Safe Configuration Tuning for Cloud Databases 2022 SIGMOD 5.8826802e-05
5,258 One Model to Rule them All: Towards Zero-Shot Learning for Databases 2022 CIDR 5.5998705e-05
5,334 LEON: A New Framework for ML-Aided Query Optimization 2023 VLDB 5.5649836e-05
5,368 Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing 2022 VLDB 5.5457532e-05
5,401 ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads 2024 VLDB 5.5285035e-05
5,423 Kepler: Robust Learning for Faster Parametric Query Optimization 2023 SIGMOD 5.5130233e-05
5,640 AutoSteer: Learned Query Optimization for Any SQL Database 2023 VLDB 5.3933314e-05
5,832 Stage: Query Execution Time Prediction in Amazon Redshift 2024 SIGMOD 5.3111109e-05
5,942 SAM: Database Generation from Query Workloads with Supervised Autoregressive Models 2022 SIGMOD 5.2634242e-05
5,951 PGMJoins: Random Join Sampling with Graphical Models 2021 SIGMOD 5.2592385e-05
5,972 SafeBound: A Practical System for Generating Cardinality Bounds 2023 SIGMOD 5.2474768e-05
6,040 Steering Query Optimizers: A Practical Take on Big Data Workloads 2021 SIGMOD 5.2412035e-05
6,297 Towards instance-optimized data systems 2021 VLDB 5.1227886e-05
6,368 Pre-training Summarization Models of Structured Datasets for Cardinality Estimation 2022 VLDB 5.0937722e-05
6,383 Sample-Efficient Cardinality Estimation Using Geometric Deep Learning 2024 VLDB 5.0884322e-05
6,685 How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks 2025 SIGMOD 4.9627485e-05
6,775 A Unified Transferable Model for ML-Enhanced DBMS 2022 CIDR 4.9299192e-05
6,879 Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data 2023 SIGMOD 4.8971368e-05
6,885 PilotScope: Steering Databases with Machine Learning Drivers 2024 VLDB 4.895386e-05
6,969 LpBound: Pessimistic Cardinality Estimation using ℓp-Norms of Degree Sequences 2025 SIGMOD 4.8799937e-05
7,008 Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective 2024 VLDB 4.8643538e-05
7,123 ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation 2024 SIGMOD 4.8251036e-05
7,126 Debunking the Myth of Join Ordering: Toward Robust SQL Analytics 2025 SIGMOD 4.8232367e-05
7,179 Coresets over Multiple Tables for Feature-rich and Data-efficient Machine Learning 2023 VLDB 4.8078895e-05
7,221 Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation 2023 SIGMOD 4.797194e-05
7,336 Refactoring Index Tuning Process with Benefit Estimation 2024 VLDB 4.7599411e-05
7,828 Modeling Shifting Workloads for Learned Database Systems 2024 SIGMOD 4.6407986e-05
7,854 dbET: Execution Time Distribution-based Plan Selection 2023 SIGMOD 4.6350172e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 28 of 28 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
1 Access Path Selection in a Relational Database Management System 1979 SIGMOD 0.0040449103
64 Improved Histograms for Selectivity Estimation of Range Predicates 1996 SIGMOD 0.00063612837
66 Spark SQL: Relational Data Processing in Spark 2015 SIGMOD 0.00061639801
71 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059038975
102 The Case for Learned Index Structures 2018 SIGMOD 0.00049545203
121 Improved Query Performance with Variant Indexes 1997 SIGMOD 0.00045447517
141 Selectivity Estimation Without the Attribute Value Independence Assumption 1997 VLDB 0.00041786333
182 LEO - DB2's LEarning Optimizer 2001 VLDB 0.00036962631
204 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00034784455
333 Neo: A Learned Query Optimizer 2019 VLDB 0.00027206884
372 Selectivity Estimation using Probabilistic Models 2001 SIGMOD 0.00025354779
405 Approximate Query Processing Using Wavelets 2000 VLDB 0.00024057494
608 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00019235898
758 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.0001706608
806 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.00016434274
842 Independence is Good: Dependency-Based Histogram Synopses for High-Dimensional Data 2001 SIGMOD 0.00016031973
943 Wander Join: Online Aggregation via Random Walks 2016 SIGMOD 0.00015145883
1,105 Cardinality Estimation Done Right: Index-Based Join Sampling 2017 CIDR 0.00013990395
1,254 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00013027411
1,369 Random Sampling over Joins Revisited 2018 SIGMOD 0.00012339777
1,547 Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions 2011 VLDB 0.00011442359
1,611 Qd-tree: Learning Data Layouts for Big Data Analytics 2020 SIGMOD 0.00011147324
1,737 QuickSel: Quick Selectivity Learning with Mixture Models 2020 SIGMOD 0.00010720294
2,083 Towards a Learning Optimizer for Shared Clouds 2019 VLDB 9.5834572e-05
2,165 Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation 2015 SIGMOD 9.389622e-05
2,219 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2019 SIGMOD 9.2623533e-05
2,865 Designing Succinct Secondary Indexing Mechanism by Exploiting Column Correlations 2019 SIGMOD 7.9862595e-05
2,969 Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models 2017 VLDB 7.7974762e-05
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