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Automatically Indexing Millions of Databases in Microsoft Azure SQL Database

Summary: Industrial-strength auto-indexing service for Azure SQL Database that auto-recommends and applies indexes across millions of databases, enabling broad deployment and notable performance gains. Describes architecture, design choices, implementation, and large-scale production validation on real workloads. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h7b490f9e26889b8b
Venue
SIGMOD
Year
2019
Pagerank
0.00010385462
Overall Rank
1,517 | 89.84%
DOI
10.1145/3299869.3314035

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{das_sigmod19,
        title = {{Automatically Indexing Millions of Databases in Microsoft Azure SQL Database}},
        author = {Das, Sudipto and Grbic, Miroslav and Ilic, Igor and Jovandic, Isidora and Jovanovic, Andrija and Narasayya, Vivek R. and Radulovic, Miodrag and Stikic, Maja and Xu, Gaoxiang and Chaudhuri, Surajit},
        series = {{SIGMOD} '19},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3299869.3314035},
        url = {https://dl.acm.org/doi/10.1145/3299869.3314035},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

Showing 40 of 40 citing papers.

Rank Citing Paper Year Venue Pagerank
1,282 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011197535
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
1,771 Diagnosing Root Causes of Intermittent Slow Queries in Cloud Databases 2020 VLDB 9.6775181e-05
2,290 Active Learning for ML Enhanced Database Systems 2020 SIGMOD 8.6813363e-05
2,654 Towards Cost-Effective and Elastic Cloud Database Deployment via Memory Disaggregation 2021 VLDB 8.1466759e-05
3,328 Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift 2023 SIGMOD 7.4094448e-05
3,486 HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements 2022 SIGMOD 7.2428834e-05
3,489 Cosine: A Cloud-Cost Optimized Self-Designing Key-Value Storage Engine 2022 VLDB 7.2421958e-05
3,575 Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation 2021 VLDB 7.1769215e-05
3,959 MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems 2021 SIGMOD 6.8804723e-05
4,022 Automated Generation of Materialized Views in Oracle 2020 VLDB 6.8345671e-05
4,278 MorphoSys: Automatic Physical Design Metamorphosis for Distributed Database Systems 2020 VLDB 6.6739278e-05
4,489 Real-time Workload Pattern Analysis for Large-scale Cloud Databases 2023 VLDB 6.5619575e-05
4,726 Learned Index Benefits: Machine Learning Based Index Performance Estimation 2022 VLDB 6.4329878e-05
4,990 Budget-aware Index Tuning with Reinforcement Learning 2022 SIGMOD 6.3120056e-05
5,208 PolarDB-MP: A Multi-Primary Cloud-Native Database via Disaggregated Shared Memory 2024 SIGMOD 6.215627e-05
5,413 Flexible Resource Allocation for Relational Database-as-a-Service 2023 VLDB 6.1283496e-05
5,645 ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning 2022 SIGMOD 6.0354456e-05
5,687 HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning 2023 VLDB 6.0201937e-05
6,121 Breaking It Down: An In-depth Study of Index Advisors 2024 VLDB 5.863893e-05
6,768 Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities 2022 SIGMOD 5.6693759e-05
7,257 RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems 2025 VLDB 5.5579707e-05
7,368 PolarDB-SCC: A Cloud-Native Database Ensuring Low Latency for Strongly Consistent Reads 2023 VLDB 5.526328e-05
7,715 Tastes Great! Less Filling! High Performance and Accurate Training Data Collection for Self-Driving Database Management Systems 2022 SIGMOD 5.4556951e-05
7,921 DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning 2022 VLDB 5.4098206e-05
7,997 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 5.3938336e-05
8,798 Automatic Indexing in Oracle 2025 VLDB 5.2606925e-05
8,902 Tiresias: Enabling Predictive Autonomous Storage and Indexing 2022 VLDB 5.2387388e-05
9,067 Bringing Cloud-Native Storage to SAP IQ 2021 SIGMOD 5.2134185e-05
9,154 Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems 2024 VLDB 5.2050937e-05
9,385 Automatic SQL Error Mitigation in Oracle 2023 VLDB 5.1697992e-05
9,655 Db2une: Tuning Under Pressure via Deep Learning 2024 VLDB 5.1307018e-05
9,731 Database Gyms 2023 CIDR 5.120066e-05
10,293 From Scale-Up to Scale-Out: PolarDB’s Journey to Achieving 2 Billion tpmC 2025 VLDB 5.031399e-05
10,676 Understanding and Detecting Query Performance Regression in Practical Index Tuning: [Experiments & Analysis] 2026 SIGMOD 4.9605343e-05
10,787 DBAIOps: A Reasoning LLM-Enhanced Database Operation and Maintenance System using Knowledge Graphs 2026 VLDB 4.9605343e-05
10,986 AutoLiquid: Autonomic Data Layout Optimization for the Databricks Lakehouse 2026 VLDB 4.9605343e-05
10,988 Evaluating the Practical Effectiveness of LLM-Driven Index Tuning on Microsoft SQL Server 2026 VLDB 4.9605343e-05
11,207 Automated Database Tuning vs. Human-Based Tuning in a Simulated Stressful Work Environment: A Demonstration of the Database Gym 2025 SIGMOD 4.9605343e-05
11,443 SQL:Trek Automated Index Design at Airbnb 2025 VLDB 4.9605343e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 15 of 15 cited papers.

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

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