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Automatic Database Management System Tuning Through Large-scale Machine Learning

Summary: Automated DBMS tuning via large-scale ML (OtterTune) to select impactful knobs, map unseen workloads to known ones, and recommend settings. Evaluated on three DBMSs; achieves configurations as good as or better than existing tools or human experts. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h2102c219f1cf4d9c
Venue
SIGMOD
Year
2017
Pagerank
0.00036675568
Overall Rank
78 | 99.48%
DOI
10.1145/3035918.3064029

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{aken_sigmod17,
        title = {{Automatic Database Management System Tuning Through Large-scale Machine Learning}},
        author = {Van Aken, Dana and Pavlo, Andrew and Gordon, Geoffrey J. and Zhang, Bohan},
        series = {{SIGMOD} '17},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3035918.3064029},
        url = {https://dl.acm.org/doi/10.1145/3035918.3064029},
        year = {2017}
}

Incoming Citations (Sorted by Pagerank)

Showing 50 of 155 citing papers.

Rank Citing Paper Year Venue Pagerank
85 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035876108
314 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00021276452
437 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00018310278
555 SageDB: A Learned Database System 2019 CIDR 0.0001650754
1,128 Qd-tree: Learning Data Layouts for Big Data Analytics 2020 SIGMOD 0.00011901941
1,155 QuickSel: Quick Selectivity Learning with Mixture Models 2020 SIGMOD 0.00011777046
1,245 DB-BERT: A Database Tuning Tool that "Reads the Manual" 2022 SIGMOD 0.0001136308
1,280 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011224914
1,289 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB 0.00011159167
1,432 Towards a Learning Optimizer for Shared Clouds 2019 VLDB 0.00010676754
1,512 Cloud-Native Database Systems at Alibaba: Opportunities and Challenges 2019 VLDB 0.00010425349
1,525 Updatable Learned Index with Precise Positions 2021 VLDB 0.00010355133
1,606 The Data Calculator*: Data Structure Design and Cost Synthesis from First Principles and Learned Cost Models 2018 SIGMOD 0.00010091937
1,699 Black or White? How to Develop an AutoTuner for Memory-based Analytics 2020 SIGMOD 9.8403606e-05
1,849 Diagnosing Root Causes of Intermittent Slow Queries in Cloud Databases 2020 VLDB 9.5032324e-05
1,891 Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn 2019 CIDR 9.4233024e-05
2,002 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 9.2076835e-05
2,227 GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization 2024 VLDB 8.8007923e-05
2,278 Active Learning for ML Enhanced Database Systems 2020 SIGMOD 8.7057608e-05
2,583 Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation 2021 VLDB 8.2589842e-05
2,721 ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases 2021 SIGMOD 8.0931221e-05
2,765 Instance-Optimized Data Layouts for Cloud Analytics Workloads 2021 SIGMOD 8.0401855e-05
2,770 Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation 2022 VLDB 8.0343719e-05
2,880 Optimal Column Layout for Hybrid Workloads 2019 VLDB 7.9118308e-05
2,908 AI Meets Database: AI4DB and DB4AI 2021 SIGMOD 7.8716173e-05
3,029 Autoscaling Tiered Cloud Storage in Anna 2019 VLDB 7.7341355e-05
3,032 iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases 2019 VLDB 7.7317595e-05
3,052 LlamaTune: Sample-Efficient DBMS Configuration Tuning 2022 VLDB 7.704739e-05
3,159 CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions 2021 VLDB 7.5797912e-05
3,171 Panda: Performance Debugging for Databases using LLM Agents 2024 CIDR 7.5661555e-05
3,404 Native Store Extension for SAP HANA 2019 VLDB 7.3257341e-05
3,430 A Demonstration of the OtterTune Automatic Database Management System Tuning Service 2018 VLDB 7.3022151e-05
3,480 Cosine: A Cloud-Cost Optimized Self-Designing Key-Value Storage Engine 2022 VLDB 7.2661848e-05
3,487 HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements 2022 SIGMOD 7.2603973e-05
3,518 A Comparative Evaluation of Systems for Scalable Linear Algebra-based Analytics 2018 VLDB 7.236638e-05
3,525 Key-Value Storage Engines 2020 SIGMOD 7.2293566e-05
3,565 Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift 2023 SIGMOD 7.200937e-05
3,588 Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation 2021 VLDB 7.1841858e-05
3,632 VISTA: Optimized System for Declarative Feature Transfer from Deep CNNs at Scale 2020 SIGMOD 7.146238e-05
3,672 Leaper: A Learned Prefetcher for Cache Invalidation in LSM-tree based Storage Engines 2020 VLDB 7.1084283e-05
3,680 openGauss: An Autonomous Database System 2021 VLDB 7.1016555e-05
3,948 Deploying a Steered Query Optimizer in Production at Microsoft 2022 SIGMOD 6.9051584e-05
3,964 MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems 2021 SIGMOD 6.889374e-05
4,080 Towards Dynamic and Safe Configuration Tuning for Cloud Databases 2022 SIGMOD 6.8151596e-05
4,113 Automatic Database Configuration Debugging using Retrieval-Augmented Language Models 2025 SIGMOD 6.7964307e-05
4,459 Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process 2022 SIGMOD 6.5883555e-05
4,618 The Price of Tailoring the Index to Your Data: Poisoning Attacks on Learned Index Structures 2022 SIGMOD 6.4981355e-05
4,668 Intelligent Scaling in Amazon Redshift 2024 SIGMOD 6.4768105e-05
4,743 Machine Learning for Databases 2021 VLDB 6.4379536e-05
4,779 Learned Approximate Query Processing: Make it Light, Accurate and Fast 2021 CIDR 6.416435e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

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