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Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation

Summary: NoisePage demonstrates a self-driving DBMS that auto-tunes itself with ML. Three ML-based components—workload forecasting, behavior modeling, and action planning—drive holistic autonomous operation and faster convergence to stable configurations. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12720
Venue
VLDB
Year
2021
Pagerank
7.2834069e-05
Overall Rank
3,586 | 75.40%
DOI
10.14778/3476311.3476411

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{pavlo_vldb21,
        title = {{Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation}},
        author = {Pavlo, Andrew and Butrovich, Matthew and Ma, Lin and Menon, Prashanth and Lim, Wan Shen and Van Aken, Dana and Zhang, William},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {12},
        pages = {3211--3221},
        doi = {10.14778/3476311.3476411},
        url = {https://doi.org/10.14778/3476311.3476411},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 19 of 19 citing papers.

Rank Citing Paper Year Venue Pagerank
2,298 GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization 2024 VLDB 8.7886538e-05
2,740 Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation 2022 VLDB 8.1855759e-05
3,343 LlamaTune: Sample-Efficient DBMS Configuration Tuning 2022 VLDB 7.4983591e-05
3,757 Panda: Performance Debugging for Databases using LLM Agents 2024 CIDR 7.1483644e-05
6,462 PilotScope: Steering Databases with Machine Learning Drivers 2024 VLDB 5.8717744e-05
6,480 Proteus: Autonomous Adaptive Storage for Mixed Workloads 2022 SIGMOD 5.8669819e-05
7,755 Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD 2024 VLDB 5.5519655e-05
7,757 CAMAL: Optimizing LSM-trees via Active Learning 2024 SIGMOD 5.5508469e-05
7,846 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 5.5331459e-05
8,042 Grep: A Graph Learning Based Database Partitioning System 2023 SIGMOD 5.5015896e-05
8,193 Towards Building Autonomous Data Services on Azure 2023 SIGMOD 5.4696038e-05
8,323 SageDB: An Instance-Optimized Data Analytics System 2022 VLDB 5.4539294e-05
8,984 Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems 2024 VLDB 5.3395569e-05
9,536 Database Gyms 2023 CIDR 5.2529727e-05
9,654 Automating the Enterprise with Foundation Models 2024 VLDB 5.2422003e-05
10,066 Check Out the Big Brain on BRAD: Simplifying Cloud Data Processing with Learned Automated Data Meshes 2023 VLDB 5.1643809e-05
10,340 AgentTune: An Agent-Based Large Language Model Framework for Database Knob Tuning 2026 SIGMOD 5.093636e-05
10,506 This is Going to Sound Crazy, But What If We Used Large Language Models to Boost Automatic Database Tuning Algorithms By Leveraging Prior History? We Will Find Better Configurations More Quickly Than Retraining From Scratch! 2026 SIGMOD 5.093636e-05
10,706 Automated Database Tuning vs. Human-Based Tuning in a Simulated Stressful Work Environment: A Demonstration of the Database Gym 2025 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 38 of 38 cited papers.

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

Rank Cited Paper Year Venue Pagerank
86 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00035316107
87 Automated Selection of Materialized Views and Indexes for SQL Databases 2000 VLDB 0.00035281619
100 LEO - DB2's LEarning Optimizer 2001 VLDB 0.00034385207
156 An Efficient, Cost-Driven Index Selection Tool for Microsoft SQL Server 1997 VLDB 0.00028636811
184 DB2 Design Advisor: Integrated Automatic Physical Database Design 2004 VLDB 0.00026256101
199 Integrating Vertical and Horizontal Partitioning into Automated Physical Database Design 2004 SIGMOD 0.00025612088
234 Self-Driving Database Management Systems 2017 CIDR 0.00023810722
246 Automating Physical Database Design in a Parallel Database 2002 SIGMOD 0.00023457421
259 Database Cracking 2007 CIDR 0.00023119313
334 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00020875082
347 Tuning Database Configuration Parameters with iTuned 2009 VLDB 0.00020651582
378 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00019638121
461 Query-based Workload Forecasting for Self-Driving Database Management Systems 2018 SIGMOD 0.00018068441
471 Skew-Aware Automatic Database Partitioning in Shared-Nothing, Parallel OLTP Systems 2012 SIGMOD 0.0001793564
498 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00017440583
523 Adaptive Self-Tuning Memory in DB2 2006 VLDB 0.00017133451
563 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.0001650812
600 Rethinking Database System Architecture: Towards a Self-tuning RISC-style Database System 2000 VLDB 0.00015871387
625 Automatic Performance Diagnosis and Tuning in Oracle 2005 CIDR 0.0001566968
781 Self-tuning Database Technology and Information Services: from Wishful Thinking to Viable Engineering 2002 VLDB 0.00014085674
854 Index Selection in a Self-Adaptive Data Base Management System 1976 SIGMOD 0.00013581028
1,092 Automated Demand-driven Resource Scaling in Relational Database-as-a-Service 2016 SIGMOD 0.00012221946
1,199 Bridging the Archipelago between Row-Stores and Column-Stores for Hybrid Workloads 2016 SIGMOD 0.00011703966
1,266 Compressing SQL Workloads 2002 SIGMOD 0.00011412078
1,344 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB 0.00011094717
1,367 H2O: A Hands-free Adaptive Store 2014 SIGMOD 0.00011014419
1,548 Automatically Indexing Millions of Databases in Microsoft Azure SQL Database 2019 SIGMOD 0.00010392475
1,706 SQL Memory Management in Oracle9i 2002 VLDB 9.9628446e-05
1,831 On Predictive Modeling for Optimizing Transaction Execution in Parallel OLTP Systems 2012 VLDB 9.6635729e-05
1,852 Automated Partitioning Design in Parallel Database Systems 2011 SIGMOD 9.6134443e-05
1,931 Performance and Resource Modeling in Highly-Concurrent OLTP Workloads 2013 SIGMOD 9.4664741e-05
2,313 Active Learning for ML Enhanced Database Systems 2020 SIGMOD 8.762627e-05
2,812 Query Performance Prediction for Concurrent Queries using Graph Embedding 2020 VLDB 8.0979597e-05
3,213 Estimating Cardinalities with Deep Sketches 2019 SIGMOD 7.6328677e-05
3,346 CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions 2021 VLDB 7.4967834e-05
3,400 A Demonstration of the OtterTune Automatic Database Management System Tuning Service 2018 VLDB 7.4433294e-05
3,961 MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems 2021 SIGMOD 6.987575e-05
8,068 Demonstrating UDO: A Unified Approach for Optimizing Transaction Code, Physical Design, and System Parameters via Reinforcement Learning 2021 SIGMOD 5.4941082e-05
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