TITLE:
Interoperability in Data Management: A Comparative Study of Distributed and Federated Database Systems
AUTHORS:
Waqar Ahmad
KEYWORDS:
Distributed Database Systems, Federated Database Systems, Interoperability, Schema Autonomy, Data Replication, Query Optimization, Fault Tolerance
JOURNAL NAME:
American Journal of Industrial and Business Management,
Vol.16 No.9,
September
18,
2026
ABSTRACT: This study compares Distributed Database Systems (DDBS) and Federated Database Systems (FDBS) in data management. Modern DDBS, including NoSQL and NewSQL platforms, offer scalability, elasticity, and operational flexibility without assuming specific workload characteristics. Their component architecture accommodates homogeneous and heterogeneous configurations for diverse requirements in large-scale information systems. An FDBS maintains a global schema, translating global queries into local queries and amalgamating local results to present a unified global view; it addresses the complexities of integrating and managing diverse data from multiple autonomous sources. The choice between these paradigms depends on specific use cases and organizational needs. Distributed databases excel in scenarios that prioritize data distribution, replication, and concurrency control, offering higher availability and performance under favorable workload and replication conditions. Federated systems, by contrast, are valuable in situations that demand seamless data exchange and pooled analyses across heterogeneous sources. They accommodate diverse data models, data definitions, and manipulation facilities, and transaction management while preserving the autonomy of participating databases. Despite their advantages, federated systems introduce complexities related to transaction determinism in specific deterministic designs, transaction aborts, and potential latency. This review elucidates the distinctive attributes of both paradigms across architecture, scalability, fault tolerance, query optimization, and security, and identifies directions for future research on interoperable data management.