Survivability of Cloud Databases - Factors and Prediction
Summary: Large-scale survivability study of Azure SQL DB examines cloud-database lifespan before being dropped. Identifies predictive factors of lifespan and shows practical uses to boost efficiency and customer experience in cloud DB services. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jose Picado
- 2. Willis Lang
- 3. Edward C. Thayer
Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,376 | Moneyball: Proactive Auto-Scaling in Microsoft Azure SQL Database Serverless | 2022 | VLDB | 8.9367999e-05 |
| 5,574 | Solver-In-The-Loop Cluster Resource Management for Database-as-a-Service | 2023 | VLDB | 5.4264731e-05 |
| 6,066 | Flexible Resource Allocation for Relational Database-as-a-Service | 2023 | VLDB | 5.225259e-05 |
| 6,702 | Tenant Placement in Over-subscribed Database-as-a-Service Clusters | 2022 | VLDB | 4.9518701e-05 |
| 7,044 | Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation | 2021 | VLDB | 4.8475963e-05 |
| 8,490 | SA-LSM: Optimize Data Layout for LSM-tree Based Storage using Survival Analysis | 2022 | VLDB | 4.494994e-05 |
| 10,934 | Proactive Resume and Pause of Resources for Microsoft Azure SQL Database Serverless | 2024 | SIGMOD | 4.1905499e-05 |
| 11,491 | Toto - Benchmarking the Efficiency of a Cloud Service | 2021 | SIGMOD | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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