Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{206592,
        author = {Dhanush M and Chirag and Rakshan R and Muhammad Sinan PK and Ganapathi Sharma K},
        title = {PolygloDB: An Intelligent Polyglot Database Service with Automatic Data Partitioning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {66-73},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206592},
        abstract = {Ultramodern software operations deal with a large spectrum of data types—from well-structured relational records to roughly organized JSON loads to free-form textbooks. Since no single database machine is equally effective in handling all these data formats, the engineering brigades are progressively abandoning the polyglot continuity design principle, which in- volves keeping several storehouse machines operational simultaneously. However, deciding and assigning the appropriate data- base for each data type is a homemade, moxie-dependent task. Misassignments in that respect are expensive and degrade query performance, erode transactional guarantees, and bloat functional outflow. This paper presents PolygloDB, a middleware sublayer that eliminates the guesswork in database selection by sketching incoming data and routing it automatically to the most appropriate backend: PostgreSQL for relational records, MongoDB for semi- structured documents, and Elasticsearch for textbook-heavy con- tent. Routing decisions are based on a binary-mode decision ma- chine that couple’s deterministic rule-based heuristics with a trained machine-learning classifier, thus marrying speed and flexibility. A centralized Metadata roster records every placement decision so that a subsequent Query Router can retrieve data from whichever backends hold it, giving the visitor a single uniform answer. Standard results show that PolygloDB achieves superior query performance, selection delicacy, and lower inventor trouble than single-database birth and rule-only routing strategy.},
        keywords = {Polyglot Persistence, Automatic Data Partitioning, Hybrid Decision Engine, Federated Query Execution, Metadata Catalog, Database Management Systems},
        month = {July},
        }