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Evaluating the Practical Effectiveness of LLM-Driven Index Tuning on Microsoft SQL Server

Summary: Empirical study of LLM-based index tuning for SQL Server across benchmarks and enterprise workloads, compared with DTA. LLMs sometimes achieve substantially faster execution, but exhibit high variance and often worse optimizer-estimated costs, complicating hybrid advisors. (summarized by gpt-5.6-luna on Aug 28 2026)

Paper ID
h9ee2968f11257219
Venue
VLDB
Year
2026
Pagerank
4.9605343e-05
Overall Rank
10,988 | 26.35%
DOI
10.14778/3827998.3828015
PDF
Download (CC BY-NC-ND 4.0)

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Authors

BibTeX Citation

@article{wang_vldb26,
        title = {{Evaluating the Practical Effectiveness of LLM-Driven Index Tuning on Microsoft SQL Server}},
        author = {Wang, Xiaoying and Wu, Wentao and Narasayya, Vivek and Chaudhuri, Surajit},
        journal = {PVLDB},
        series = {{VLDB} '26},
        volume = {19},
        number = {12},
        pages = {4049--4062},
        doi = {10.14778/3827998.3828015},
        url = {https://doi.org/10.14778/3827998.3828015},
        year = {2026}
}

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Outgoing Citations (Sorted by Pagerank)

Showing 42 of 42 cited papers.

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

Rank Cited Paper Year Venue Pagerank
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061463175
74 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00037164008
91 On the Propagation of Errors in the Size of Join Results 1991 SIGMOD 0.00034691614
151 An Efficient, Cost-Driven Index Selection Tool for Microsoft SQL Server 1997 VLDB 0.00028611216
309 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.0002143249
313 Tuning Database Configuration Parameters with iTuned 2009 VLDB 0.00021288111
380 AutoAdmin "What-if" Index Analysis Utility 1998 SIGMOD 0.00019530546
411 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.0001874043
493 Database Tuning Advisor for Microsoft SQL Server 2005 2004 VLDB 0.0001735831
545 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.0001657599
756 Automatic Physical Database Tuning: A Relaxation-based Approach 2005 SIGMOD 0.00014209974
1,064 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012181459
1,246 Compressing SQL Workloads 2002 SIGMOD 0.00011355447
1,261 Sampling-Based Query Re-Optimization 2016 SIGMOD 0.00011289724
1,282 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011197535
1,294 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB 0.00011129451
1,400 Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms 2020 VLDB 0.00010759064
1,517 Automatically Indexing Millions of Databases in Microsoft Azure SQL Database 2019 SIGMOD 0.00010385462
1,656 D-Bot: Database Diagnosis System using Large Language Models 2024 VLDB 9.948529e-05
1,823 CoPhy: A Scalable, Portable, and Interactive Index Advisor for Large Workloads 2011 VLDB 9.5457638e-05
1,956 LLM-R^2: A Large Language Model Enhanced Rule-based Rewrite System for Boosting Query Efficiency 2025 VLDB 9.2927535e-05
2,290 Active Learning for ML Enhanced Database Systems 2020 SIGMOD 8.6813363e-05
3,057 LlamaTune: Sample-Efficient DBMS Configuration Tuning 2022 VLDB 7.6865211e-05
3,158 GenRewrite: Query Rewriting via Large Language Models 2026 SIGMOD 7.5676704e-05
3,172 CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions 2021 VLDB 7.5556865e-05
3,818 Comprehensive and Efficient Workload Compression 2021 VLDB 6.983427e-05
4,383 R-Bot: An LLM-based Query Rewrite System 2025 VLDB 6.6140223e-05
4,990 Budget-aware Index Tuning with Reinforcement Learning 2022 SIGMOD 6.3120056e-05
5,450 Materialized View and Index Selection Tool for Microsoft SQL Server 2000 2001 SIGMOD 6.1103095e-05
5,645 ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning 2022 SIGMOD 6.0354456e-05
6,121 Breaking It Down: An In-depth Study of Index Advisors 2024 VLDB 5.863893e-05
6,584 Can Large Language Models Be Query Optimizer for Relational Databases? 2026 SIGMOD 5.72395e-05
7,094 Plan Stitch: Harnessing the Best of Many Plans 2018 VLDB 5.5863735e-05
7,388 Towards Foundation Database Models 2025 CIDR 5.5211011e-05
7,768 DBG-PT: A Large Language Model Assisted Query Performance Regression Debugger 2024 VLDB 5.4392507e-05
7,921 DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning 2022 VLDB 5.4098206e-05
8,798 Automatic Indexing in Oracle 2025 VLDB 5.2606925e-05
9,754 Leveraging Query Optimizers to Verify the Soundness of LLM-based Query Rewrites for Real-World Workloads, and More! 2026 CIDR 5.115551e-05
9,829 Wii: Dynamic Budget Reallocation In Index Tuning 2024 SIGMOD 5.1066866e-05
9,983 Wred: Workload Reduction for Scalable Index Tuning 2024 SIGMOD 5.0860177e-05
10,676 Understanding and Detecting Query Performance Regression in Practical Index Tuning: [Experiments & Analysis] 2026 SIGMOD 4.9605343e-05
11,288 Esc: An Early-Stopping Checker for Budget-aware Index Tuning 2025 VLDB 4.9605343e-05
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