Enhancing Data Consistency and Reliability in Distributed Databases on the Google Cloud Platform

Tulasiram Yadavalli

Abstract: Maintaining data consistency and reliability in distributed databases is a critical challenge for modern applications operating at scale. Traditional approaches often struggle to balance consistency, availability, and performance in geographically dispersed environments. This paper explores strategies for enhancing data consistency and reliability in distributed databases deployed on the Google Cloud Platform (GCP). Leveraging GCP services such as Cloud Spanner, Cloud SQL, and Cloud Storage, we examine techniques for ensuring strong consistency, managing data replication, and implementing robust failover mechanisms. Furthermore, this paper analyzes the trade-offs between different consistency models and their impact on application performance and availability. We present implementation code studies showcasing best practices for achieving high availability and data durability while minimizing latency in distributed database deployments on GCP.

Keywords: Distributed databases, data consistency, data reliability, Google Cloud Platform (GCP), Cloud Spanner, Cloud SQL, Cloud Storage, data replication, failover mechanisms, consistency models, high availability, data durability, latency optimization