Deterministic Consistency Models for Cloud-Hosted Open Source Relational Databases Under Multi-Region Failover

Abstract

Cloud-hosted open source relational databases are increasingly deployed across multiple geographic regions to meet high availability and low latency requirements. However, multi-region failover remains a critical source of consistency degradation. During regional outages or leader transitions, asynchronous replication delays, quorum reconfiguration, and log reconciliation can introduce transient divergence, write reordering, and recovery latency spikes. Traditional leader-based replication ensures strong consistency under stable conditions but often incurs failover delays due to election and log synchronization overhead. Quorum-based and eventually consistent approaches improve availability but tolerate temporary inconsistency and non-deterministic commit ordering. Deterministic transaction scheduling has shown promise in improving serializability and coordination efficiency, yet it is rarely integrated directly into cloud failover control mechanisms for open source SQL engines.
This paper proposes a deterministic consistency framework that integrates global pre-transaction sequencing with consensus-assisted failover coordination. The model enforces a uniform commit order across regions before execution, ensuring stable state transitions even during leader promotion or regional recovery. A prototype implementation on a cloud-deployed relational engine demonstrates reduced failover recovery time, elimination of write reordering events, and competitive throughput compared to conventional consensus-based replication. Experimental evaluation under simulated wide-area latency confirms improved consistency stability without significant performance degradation.
The proposed framework bridges the gap between deterministic transaction processing and cloud multi-region failover design, offering a practical pathway toward resilient, serializable, and globally consistent open source relational databases.