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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
11859
Venue
VLDB
Year
2019
Pagerank
0.00027206884
Overall Rank
333 | 97.69%
DOI
10.14778/3342263.3342644

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 50 of 170 citing papers.

Rank Citing Paper Year Venue Pagerank
8,131 Sibyl: Forecasting Time-Evolving Query Workloads 2024 SIGMOD 4.5784634e-05
8,158 MONSOON: Multi-Step Optimization and Execution of Queries with Partially Obscured Predicates 2020 SIGMOD 4.5730772e-05
8,164 Efficiently Computing Join Orders with Heuristic Search 2023 SIGMOD 4.5718104e-05
8,220 PerfGuard: Deploying ML-for-Systems without Performance Regressions, Almost! 2021 VLDB 4.5557328e-05
8,345 SlabCity: Whole-Query Optimization using Program Synthesis 2023 VLDB 4.5426916e-05
8,416 Towards Building Autonomous Data Services on Azure 2023 SIGMOD 4.5196199e-05
8,417 The Case for Learned In-Memory Joins 2023 VLDB 4.5194164e-05
8,442 SageDB: An Instance-Optimized Data Analytics System 2022 VLDB 4.5120602e-05
8,488 Can Large Language Models Be Query Optimizer for Relational Databases? 2026 SIGMOD 4.4998609e-05
8,578 Robust and Budget-Constrained Encoding Configurations for In-Memory Database Systems 2022 VLDB 4.4923477e-05
8,582 Towards Query Optimizer as a Service (QOaaS) in a Unified LakeHouse Ecosystem: Can One QO Rule Them All? 2025 CIDR 4.492033e-05
8,615 The Case for NLP-Enhanced Database Tuning: Towards Tuning Tools that "Read the Manual" 2021 VLDB 4.484683e-05
8,659 Learned Offline Query Planning via Bayesian Optimization 2025 SIGMOD 4.4722928e-05
8,688 NeurDB: On the Design and Implementation of an AI-powered Autonomous Database 2025 CIDR 4.4673127e-05
8,774 Tiresias: Enabling Predictive Autonomous Storage and Indexing 2022 VLDB 4.4559995e-05
8,783 GEqO: ML-Accelerated Semantic Equivalence Detection 2023 SIGMOD 4.452825e-05
8,847 Towards Foundation Database Models 2025 CIDR 4.4371897e-05
8,956 T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees 2025 SIGMOD 4.4214154e-05
9,006 Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems 2024 VLDB 4.4101482e-05
9,074 Making Data Clouds Smarter at Keebo: Automated Warehouse Optimization using Data Learning 2023 SIGMOD 4.402065e-05
9,108 BASE: Bridging the Gap between Cost and Latency for Query Optimization 2023 VLDB 4.3950066e-05
9,141 Automatic SQL Error Mitigation in Oracle 2023 VLDB 4.3855791e-05
9,187 POLAR: Adaptive and Non-invasive Join Order Selection via Plans of Least Resistance 2024 VLDB 4.3780059e-05
9,194 Phoebe: A Learning-based Checkpoint Optimizer 2021 VLDB 4.3761777e-05
9,317 Are Joins over LSM-trees Ready? Take RocksDB as an Example 2025 VLDB 4.3556432e-05
9,345 LIMAO: A Framework for Lifelong Modular Learned Query Optimization 2025 VLDB 4.3536343e-05
9,587 Low Rank Learning for Offline Query Optimization 2025 SIGMOD 4.3215645e-05
9,662 Efficient Query Re-optimization with Judicious Subquery Selections 2023 SIGMOD 4.3097631e-05
9,693 ROME: Robust Query Optimization via Parallel Multi-Plan Execution 2024 SIGMOD 4.3027391e-05
9,747 Still Asking: How Good Are Query Optimizers, Really? 2025 VLDB 4.2897489e-05
9,806 The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format 2024 SIGMOD 4.2805224e-05
9,825 Athena: An Effective Learning-based Framework for Query Optimizer Performance Improvement 2025 SIGMOD 4.2751057e-05
9,827 PLATON: Top-down R-tree Packing with Learned Partition Policy 2023 SIGMOD 4.2751057e-05
9,846 HyperBlocker: Accelerating Rule-based Blocking in Entity Resolution using GPUs 2025 VLDB 4.2721228e-05
9,852 Machine Unlearning in Learned Databases: An Experimental Analysis 2024 SIGMOD 4.2714575e-05
9,869 Turbo-Charging SPJ Query Plans with Learned Physical Join Operator Selections 2022 VLDB 4.2675361e-05
9,892 DBMS Fitting: Why should we learn what we already know? 2020 CIDR 4.261445e-05
9,917 Check Out the Big Brain on BRAD: Simplifying Cloud Data Processing with Learned Automated Data Meshes 2023 VLDB 4.2561557e-05
9,930 Wii: Dynamic Budget Reallocation In Index Tuning 2024 SIGMOD 4.2510122e-05
9,957 How to Optimize SQL Queries? A Comparison Between Split, Holistic, and Hybrid Approaches 2025 VLDB 4.2373024e-05
9,960 An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL 2025 SIGMOD 4.2294678e-05
10,018 GenJoin: Conditional Generative Plan-to-Plan Query Optimizer that Learns from Subplan Hints 2026 SIGMOD 4.1945683e-05
10,087 High Performance or Low Memory? An Updatable Learned Index Framework for Time-Space Tradeoff 2026 SIGMOD 4.1945683e-05
10,112 SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer 2026 SIGMOD 4.1945683e-05
10,125 Understanding and Detecting Query Performance Regression in Practical Index Tuning: [Experiments & Analysis] 2026 SIGMOD 4.1945683e-05
10,156 Divo: Learning a Stable and Effective Query Optimizer with a Diverse Workload 2026 SIGMOD 4.1945683e-05
10,174 IDAP++: Advancing Divergence-Aware Pruning with Joint Filter and Layer Optimization 2026 SIGMOD 4.1945683e-05
10,199 R2O: A Dual-Layer Framework for Joint Rewriting and Ordering in Distributed Property Graph Query Optimization 2026 SIGMOD 4.1945683e-05
10,203 Reqo: A Comprehensive Learning-Based Cost Model for Robust and Explainable Query Optimization 2026 SIGMOD 4.1945683e-05
10,219 Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking 2026 SIGMOD 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

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

Rank Cited Paper Year Venue Pagerank
71 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059038975
102 The Case for Learned Index Structures 2018 SIGMOD 0.00049545203
182 LEO - DB2's LEarning Optimizer 2001 VLDB 0.00036962631
204 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00034784455
224 CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies 2004 SIGMOD 0.00032746205
300 Deep Learning for Entity Matching: A Design Space Exploration 2018 SIGMOD 0.00028441466
454 An Overview of Query Optimization in Relational Systems 1998 PODS 0.00022734812
629 Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors 2009 VLDB 0.00018942366
684 Towards a Robust Query Optimizer: A Principled and Practical Approach 2005 SIGMOD 0.00018179769
801 SageDB: A Learned Database System 2019 CIDR 0.00016505496
1,337 HoloDetect: Few-Shot Learning for Error Detection 2019 SIGMOD 0.00012497164
1,737 QuickSel: Quick Selectivity Learning with Mixture Models 2020 SIGMOD 0.00010720294
2,156 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2018 VLDB 9.4170209e-05
3,658 Towards a Hands-Free Query Optimizer through Deep Learning 2019 CIDR 6.8704209e-05
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