Authors: Dr. Saurabh Saoji, Aditya Deshmukh, Aadesh Gulumbe, Sanika Hingalkar, Akash Shelke
Abstract: Cloud-based applications increasingly rely on multiple database systems to handle diverse data models and workloads, yet managing these heterogeneous environments remains complex and resource-intensive. Traditional Database-as-a-Service platforms often introduce vendor lock-in, limited flexibility, and high costs, restricting their suitability for academic and research use. To address these challenges, this research proposes an open-source, AI-powered Cloud Database-as-a-Service platform that unifies the management of SQL, NoSQL, and in-memory databases using Kubernetes-based container orchestration. The system integrates AI-driven natural language assistance for schema generation and query formulation, along with real-time monitoring using Prometheus and Grafana. By combining automation, intelligent interaction, and cost-effective deployment, the platform aims to improve accessibility, efficiency, and scalability in cloud-native database management.
DOI: http://doi.org/10.5281/zenodo.20732646
