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@article{182656,
        author = {Nimisha Modi and Jayshri Patel},
        title = {Evaluating Query Processing Architectures in Relational and Document Databases},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {2},
        pages = {2732-2736},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=182656},
        abstract = {Query processing architectures in relational and document-oriented databases differ significantly in how they handle core operations like selection, sorting, and joins. Relational databases rely on fixed schemas, cost-based optimizers, and strong ACID guarantees to efficiently process complex queries with multiple joins. In contrast, document databases offer flexible schemas and horizontal scalability, using pipeline-based query execution with denormalized data models optimized for semi-structured data. This comparative analysis explores trade-offs in schema design, indexing strategies, query optimization, scalability, and consistency, providing insights to help choose the best database system for specific application needs.},
        keywords = {Query Processing, Relational Databases, Document Databases, Schema Flexibility, Database Scalability.},
        month = {January},
        }