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: 0.0001219157
Overall Rank: 1,067 | 92.83%
DOI: 10.1145/2882903.2903733

Incoming Non-self Citations Over Time

Authors

1. Sudipto Das (Microsoft)
2. Feng Li (Microsoft)
3. Vivek R. Narasayya (Microsoft)
4. Arnd Christian König (Microsoft)

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	0.00024013745
460	Query-based Workload Forecasting for Self-Driving Database Management Systems	2018	SIGMOD	0.00017842695
1,513	Cloud-Native Database Systems at Alibaba: Opportunities and Challenges	2019	VLDB	0.00010429438
1,994	Moneyball: Proactive Auto-Scaling in Microsoft Azure SQL Database Serverless	2022	VLDB	9.2176321e-05
2,908	AI Meets Database: AI4DB and DB4AI	2021	SIGMOD	7.8742664e-05
3,032	iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases	2019	VLDB	7.7351139e-05
3,590	Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation	2021	VLDB	7.1865343e-05
3,641	Nova-LSM: A Distributed, Component-based LSM-tree Key-value Store	2021	SIGMOD	7.1439198e-05
3,682	openGauss: An Autonomous Database System	2021	VLDB	7.1013922e-05
4,399	Adaptive HTAP through Elastic Resource Scheduling	2020	SIGMOD	6.6152806e-05
4,741	Machine Learning for Databases	2021	VLDB	6.4410027e-05
5,766	Survivability of Cloud Databases - Factors and Prediction	2018	SIGMOD	6.0025753e-05
6,753	Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities	2022	SIGMOD	5.6904085e-05
6,901	Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation	2021	VLDB	5.6520335e-05
7,179	MgCrab: Transaction Crabbing for Live Migration in Deterministic Database Systems	2019	VLDB	5.5930043e-05
8,352	Towards Building Autonomous Data Services on Azure	2023	SIGMOD	5.3488341e-05
8,371	A system design for elastically scaling transaction processing engines in virtualized servers	2020	VLDB	5.3448014e-05
9,075	Vertically Autoscaling Monolithic Applications with CaaSPER: Scalable Container-as-a-Service Performance Enhanced Resizing Algorithm for the Cloud	2024	SIGMOD	5.2283159e-05
9,706	Database Gyms	2023	CIDR	5.1376763e-05
9,737	Kora: A Cloud-Native Event Streaming Platform For Kafka	2023	VLDB	5.1349531e-05
9,959	Lorentz: Learned SKU Recommendation Using Profile Data (DMDS)	2024	SIGMOD	5.1038322e-05
10,224	Modeling Concurrency Control as a Learnable Function	2026	SIGMOD	5.0571508e-05
10,943	Lakebase: Serverless Postgres over Open Lake Storage	2026	VLDB	4.9793485e-05
11,129	Oceanus: Enable SLO-Aware Vertical Autoscaling for Cloud-Native Streaming Services in Tencent	2025	SIGMOD	4.9793485e-05
11,498	Proactive Resume and Pause of Resources for Microsoft Azure SQL Database Serverless	2024	SIGMOD	4.9793485e-05
11,613	OptScaler: A Collaborative Framework for Robust Autoscaling in the Cloud	2024	VLDB	4.9793485e-05
11,992	Toto - Benchmarking the Efficiency of a Cloud Service	2021	SIGMOD	4.9793485e-05

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.

Rank	Cited Paper	Year	Venue	Pagerank
508	Adaptive Self-Tuning Memory in DB2	2006	VLDB	0.00017089907
585	Workload-Aware Database Monitoring and Consolidation	2011	SIGMOD	0.00015949541
629	Performance Prediction for Concurrent Database Workloads	2011	SIGMOD	0.00015429949
682	Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques	2012	VLDB	0.0001481781
835	Automatic Virtual Machine Configuration for Database Workloads	2008	SIGMOD	0.00013573201
1,338	SQLVM: Performance Isolation in Multi-Tenant Relational Database-as-a-Service	2013	CIDR	0.00010979494
1,939	Performance and Resource Modeling in Highly-Concurrent OLTP Workloads	2013	SIGMOD	9.3331247e-05
3,237	Characterizing Tenant Behavior for Placement and Crisis Mitigation in Multitenant DBMSs	2013	SIGMOD	7.5017163e-05
4,774	Automated and On-Demand Provisioning of Virtual Machines for Database Applications	2007	SIGMOD	6.4199816e-05

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#	Overall Rank	Paper	Year	Venue
1	1,338	SQLVM: Performance Isolation in Multi-Tenant Relational Database-as-a-Service	2013	CIDR
2	9,899	Towards Database Virtualization for Database as a Service	2013	VLDB
3	10,919	ScaleSense: Cost-Intelligent Scaling Framework via Learned Resource Estimation in Alibaba AnalyticDB	2026	VLDB
4	2,283	CPU Sharing Techniques for Performance Isolation in Multi-tenant Relational Database-as-a-Service	2014	VLDB
5	1,994	Moneyball: Proactive Auto-Scaling in Microsoft Azure SQL Database Serverless	2022	VLDB
6	5,087	Releasing Cloud Databases from the Chains of Performance Prediction Models	2017	CIDR
7	11,498	Proactive Resume and Pause of Resources for Microsoft Azure SQL Database Serverless	2024	SIGMOD
8	5,836	Tenant Placement in Over-subscribed Database-as-a-Service Clusters	2022	VLDB
9	641	Relational Cloud: A Database-as-a-Service for the Cloud	2011	CIDR
10	5,389	Flexible Resource Allocation for Relational Database-as-a-Service	2023	VLDB