Database Management in the Era of Big Data: Trends, Challenges, and Breakthroughs

Abstract

The rapid development of Big Data has profoundly transformed database management systems, necessitating novel solutions to address the escalating complexity, volume, and variety of data. This analysis examines the principal trends, difficulties, and technological advancements impacting database administration due to the rapid increase in data volume. Significant innovations, including NoSQL databases, cloud computing, distributed architectures, and AI-driven automation, have transformed the methods by which businesses store, process, and analyze extensive datasets. Nevertheless, enduring issues persist, encompassing data security concerns, scalability constraints, and the necessity for enhanced performance. This study brings together recent research to look at how modern database systems have changed over time to deal with these problems and make them more efficient, secure, and able to process data in real time. Additionally, new technologies like blockchain and edge computing are examined for their contributions to improving security and decentralization in database administration. The results underscore the significance of hybrid database models, intelligent automation, and regulatory compliance frameworks in influencing the future of database systems. As enterprises adjust to the needs of Big Data, the integration of new technologies will be essential for achieving scalable, secure, and high-performance database management systems.