A Survey on Distributed Database Systems in the Era of Big Data
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Distributed database systems have evolved to satisfy the needs of scalability, performance, and fault tolerance due to the current digital era's fast data expansion. The design concepts, benefits, and drawbacks of modern distributed database architectures—such as cloud-native systems, NoSQL, and NewSQL—are thoroughly examined in this study. With an emphasis on using artificial intelligence and machine learning approaches to improve query speed and anomaly detection, key difficulties such as data integrity, latency optimization, and safe multi-cloud integration are covered. Despite notable progress, important concerns about data privacy and synchronization in diverse settings remain, and moral leadership endures. To create more robust and accountable database systems, this study promotes a well-rounded strategy that addresses the ethical and social aspects of distributed data management and increases technical efficiency.
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