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Automated Demand-driven Resource Scaling in Relational Database-as-a-Service

Summary: Automates demand-driven auto-scaling of relational DaaS resources via robust signals from database engine telemetry to predict workload needs. Azure SQL Database prototype yields 1.5–3× cost savings with latency on par with utilization-only methods, letting tenants budget by latency rather than fixed resources. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hc0b2ae9e7b5ff9cc
Venue
SIGMOD
Year
2016
Pagerank
0.00012186505
Overall Rank
1,068 | 92.83%
DOI
10.1145/2882903.2903733

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{das_sigmod16,
        title = {{Automated Demand-driven Resource Scaling in Relational Database-as-a-Service}},
        author = {Das, Sudipto and Li, Feng and Narasayya, Vivek R. and König, Arnd Christian},
        series = {{SIGMOD} '16},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2882903.2903733},
        url = {https://dl.acm.org/doi/10.1145/2882903.2903733},
        year = {2016}
}

Incoming Citations (Sorted by Pagerank)

Showing 27 of 27 citing papers.

Rank Citing Paper Year Venue Pagerank
224 Self-Driving Database Management Systems 2017 CIDR 0.00024011047
461 Query-based Workload Forecasting for Self-Driving Database Management Systems 2018 SIGMOD 0.00017841988
1,512 Cloud-Native Database Systems at Alibaba: Opportunities and Challenges 2019 VLDB 0.00010425349
1,996 Moneyball: Proactive Auto-Scaling in Microsoft Azure SQL Database Serverless 2022 VLDB 9.213369e-05
2,908 AI Meets Database: AI4DB and DB4AI 2021 SIGMOD 7.8716173e-05
3,032 iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases 2019 VLDB 7.7317595e-05
3,588 Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation 2021 VLDB 7.1841858e-05
3,643 Nova-LSM: A Distributed, Component-based LSM-tree Key-value Store 2021 SIGMOD 7.1406131e-05
3,680 openGauss: An Autonomous Database System 2021 VLDB 7.1016555e-05
4,401 Adaptive HTAP through Elastic Resource Scheduling 2020 SIGMOD 6.6121514e-05
4,743 Machine Learning for Databases 2021 VLDB 6.4379536e-05
5,767 Survivability of Cloud Databases - Factors and Prediction 2018 SIGMOD 5.9997338e-05
6,758 Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities 2022 SIGMOD 5.6877154e-05
6,903 Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation 2021 VLDB 5.6493582e-05
7,182 MgCrab: Transaction Crabbing for Live Migration in Deterministic Database Systems 2019 VLDB 5.5903567e-05
8,357 Towards Building Autonomous Data Services on Azure 2023 SIGMOD 5.3463255e-05
8,375 A system design for elastically scaling transaction processing engines in virtualized servers 2020 VLDB 5.3423179e-05
9,084 Vertically Autoscaling Monolithic Applications with CaaSPER: Scalable Container-as-a-Service Performance Enhanced Resizing Algorithm for the Cloud 2024 SIGMOD 5.2258409e-05
9,711 Database Gyms 2023 CIDR 5.1352441e-05
9,742 Kora: A Cloud-Native Event Streaming Platform For Kafka 2023 VLDB 5.1325223e-05
9,965 Lorentz: Learned SKU Recommendation Using Profile Data (DMDS) 2024 SIGMOD 5.1014161e-05
10,230 Modeling Concurrency Control as a Learnable Function 2026 SIGMOD 5.0547568e-05
10,952 Lakebase: Serverless Postgres over Open Lake Storage 2026 VLDB 4.9769913e-05
11,138 Oceanus: Enable SLO-Aware Vertical Autoscaling for Cloud-Native Streaming Services in Tencent 2025 SIGMOD 4.9769913e-05
11,504 Proactive Resume and Pause of Resources for Microsoft Azure SQL Database Serverless 2024 SIGMOD 4.9769913e-05
11,619 OptScaler: A Collaborative Framework for Robust Autoscaling in the Cloud 2024 VLDB 4.9769913e-05
11,998 Toto - Benchmarking the Efficiency of a Cloud Service 2021 SIGMOD 4.9769913e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 9 of 9 cited papers.

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

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