This adaptive system improves user density in cloud databases, suggesting efficient resource management for multiple tenants.
We present an adaptive hibernation system for multi-tenant embedded database instances in cloud environments. The system enables thousands of user database instances to share minimal compute resources through intelligent instance lifecycle management. Our approach combines LRU-based handle caching, predictive wake scheduling, tiered hibernation states, and zero-memory hibernated state management. The system achieves 50-100x user density improvements over traditional database-per-user architectures while maintaining sub-second wake latency for 95% of requests. Key innovations include encryption-key-aware hibernation (preserving zero-knowledge guarantees), column-family-based tenant isolation with independent hibernation, and adaptive hibernation timeouts based on usage patterns and subscription tiers.
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Daniel Moya Vaca (2026) studied this question.
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