Hybrid Data Storage Architecture: A Novel Design Approach Based on Microservices Architecture

Abstract

Due to the diverse storage and performance requirements of modern data-driven environments, choosing between relational and non-relational database systems is a complex decision, as each type offers distinct advantages and limitations depending on the application. A single database system therefore fails to deliver the necessary balance of latency, scalability, and resiliency expected by contemporary workloads. One effective solution is polyglot service persistence, an approach where multiple database engines coexist within the same system to leverage the individual strengths of each. In this paper, we introduce the development of a hybrid platform that unifies several database types—together with a distributed file store—through a micro-services architecture. This strategy yields an adaptable, horizontally scalable solution capable of satisfying heterogeneous data requirements while simplifying operational overhead. Our methodology centres on a framework that exposes a unified interface to all underlying datastores, so end users can manage relational, document, and file-based data without installing or configuring each engine individually; connection logic, driver management, and schema coordination are fully abstracted. In addition, it synthesises fully documented REST APIs for every generated schema, enabling seamless CRUD operations across all underlying stores. The hybrid system is engineered to optimise every database model’s forte: transactional consistency in relational stores, elastic growth for schema-less datasets in document stores, and built-in redundancy plus fault tolerance for large files in distributed storage. Although comprehensive benchmarks are scheduled for future work, preliminary integration tests confirm that the framework streamlines deployment workflows and accelerates application development by eliminating per-database setup tasks and management.