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Neo: A Learned Query Optimizer

Summary: Neo (Neural Optimizer) uses deep neural networks to generate query execution plans, offering a learning-based alternative to hand-tuned optimizers. Bootstrapped from traditional optimizers, it learns from live queries, adapts to data patterns, is robust to estimation errors, and can match or surpass state-of-the-art engines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hb5f47951a0efd824
Venue
VLDB
Year
2019
Pagerank
0.00029114937
Overall Rank
142 | 99.05%
DOI
10.14778/3342263.3342644
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{marcus_vldb19,
        title = {{Neo: A Learned Query Optimizer}},
        author = {Marcus, Ryan and Negi, Parimarjan and Mao, Hongzi and Zhang, Chi and Alizadeh, Mohammad and Kraska, Tim and Papaemmanouil, Olga and Tatbul, Nesime},
        journal = {PVLDB},
        series = {{VLDB} '19},
        volume = {12},
        number = {11},
        pages = {1705--1718},
        doi = {10.14778/3342263.3342644},
        url = {https://doi.org/10.14778/3342263.3342644},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

Showing 50 of 180 citing papers.

Rank Citing Paper Year Venue Pagerank
4,459 Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts 2022 SIGMOD 6.5757572e-05
4,479 Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process 2022 SIGMOD 6.5665703e-05
4,489 Real-time Workload Pattern Analysis for Large-scale Cloud Databases 2023 VLDB 6.5619575e-05
4,549 One Model to Rule them All: Towards Zero-Shot Learning for Databases 2022 CIDR 6.5328866e-05
4,683 AutoSteer: Learned Query Optimization for Any SQL Database 2023 VLDB 6.4545989e-05
4,720 PreQR: Pre-training Representation for SQL Understanding 2022 SIGMOD 6.4353798e-05
4,726 Learned Index Benefits: Machine Learning Based Index Performance Estimation 2022 VLDB 6.4329878e-05
4,765 Machine Learning for Databases 2021 VLDB 6.4166895e-05
4,797 LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems 2022 SIGMOD 6.3978116e-05
4,833 Stage: Query Execution Time Prediction in Amazon Redshift 2024 SIGMOD 6.3834856e-05
5,029 COMPASS: Online Sketch-based Query Optimization for In-Memory Databases 2021 SIGMOD 6.2952031e-05
5,043 Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing 2022 VLDB 6.28918e-05
5,062 Leveraging Query Logs and Machine Learning for Parametric Query Optimization 2022 VLDB 6.2791511e-05
5,126 Steering Query Optimizers: A Practical Take on Big Data Workloads 2021 SIGMOD 6.2493606e-05
5,153 Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach 2020 SIGMOD 6.2375324e-05
5,245 FASTgres: Making Learned Query Optimizer Hinting Effective 2023 VLDB 6.1995935e-05
5,377 Can Large Language Models Predict Data Correlations from Column Names? 2023 VLDB 6.1396287e-05
5,453 Eraser: Eliminating Performance Regression on Learned Query Optimizer 2024 VLDB 6.1077838e-05
5,457 Sample-Efficient Cardinality Estimation Using Geometric Deep Learning 2024 VLDB 6.1058928e-05
5,484 A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies 2024 VLDB 6.0980944e-05
5,713 PilotScope: Steering Databases with Machine Learning Drivers 2024 VLDB 6.0090633e-05
5,728 Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data 2023 SIGMOD 5.9979958e-05
5,794 Lemo: A Cache-Enhanced Learned Optimizer for Concurrent Queries 2023 SIGMOD 5.9759435e-05
5,837 Pre-training Summarization Models of Structured Datasets for Cardinality Estimation 2022 VLDB 5.9600736e-05
5,854 Modeling Shifting Workloads for Learned Database Systems 2024 SIGMOD 5.9520525e-05
5,911 Yannakakis+: Practical Acyclic Query Evaluation with Theoretical Guarantees 2025 SIGMOD 5.9338021e-05
5,926 Quantum-Inspired Digital Annealing for Join Ordering 2024 VLDB 5.9282142e-05
5,982 Towards instance-optimized data systems 2021 VLDB 5.9096991e-05
6,109 Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective 2024 VLDB 5.8676956e-05
6,113 Expand your Training Limits! Generating Training Data for ML-based Data Management 2021 SIGMOD 5.8662826e-05
6,158 Rethinking Learned Cost Models: Why Start from Scratch? 2023 SIGMOD 5.8518237e-05
6,300 Mosaic: A Sample-Based Database System for Open World Query Processing 2020 CIDR 5.8017237e-05
6,402 A Unified Transferable Model for ML-Enhanced DBMS 2022 CIDR 5.7800842e-05
6,584 Can Large Language Models Be Query Optimizer for Relational Databases? 2026 SIGMOD 5.72395e-05
6,590 Towards Query Optimizer as a Service (QOaaS) in a Unified LakeHouse Ecosystem: Can One QO Rule Them All? 2025 CIDR 5.7233093e-05
6,646 Join Order Selection with Deep Reinforcement Learning: Fundamentals, Techniques, and Challenges 2023 VLDB 5.7053761e-05
6,672 Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation 2023 SIGMOD 5.6975871e-05
6,725 Simple Adaptive Query Processing vs. Learned Query Optimizers: Observations and Analysis 2023 VLDB 5.6826988e-05
6,768 Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities 2022 SIGMOD 5.6693759e-05
6,802 SALI: A Scalable Adaptive Learned Index Framework based on Probability Models 2023 SIGMOD 5.6623052e-05
6,812 dbET: Execution Time Distribution-based Plan Selection 2023 SIGMOD 5.6597129e-05
6,840 ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation 2024 SIGMOD 5.6513231e-05
6,906 LPLM: A Neural Language Model for Cardinality Estimation of LIKE-Queries 2024 SIGMOD 5.634971e-05
7,162 Sibyl: Forecasting Time-Evolving Query Workloads 2024 SIGMOD 5.5798063e-05
7,238 Refactoring Index Tuning Process with Benefit Estimation 2024 VLDB 5.5624225e-05
7,257 RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems 2025 VLDB 5.5579707e-05
7,347 Scalable Multi-Query Execution using Reinforcement Learning 2021 SIGMOD 5.5308106e-05
7,355 Selectivity Functions of Range Queries are Learnable* 2022 SIGMOD 5.529034e-05
7,363 Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD 2024 VLDB 5.5279826e-05
7,377 PerfGuard: Deploying ML-for-Systems without Performance Regressions, Almost! 2021 VLDB 5.5238616e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

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