In recent years, several new research initiatives have been undertaken to further improve the performance and functionality of database management systems. One of the most notable developments has been the integration of machine learning algorithms into database management systems. These algorithms help in predicting trends, identifying patterns, and making recommendations based on the data stored in the database.
Introduction:
Database management has been a critical aspect of organizations for decades now. It involves the use of software tools and techniques to store, retrieve, and manage large amounts of data efficiently. The advancement in technology and the increasing amounts of data generated every day has led to the development of advanced database management systems that are capable of handling complex data structures and large amounts of data.Another area of research is the use of cloud-based database management systems, which provide scalability, flexibility, and cost-effectiveness to organizations. These systems use cloud computing technologies to store and manage large amounts of data and make it available to users from anywhere in the world.
Keywords:
- Database management
- Advanced database management systems
- Machine learning algorithms
- Cloud-based database management
- Scalability
- Flexibility
- Cost-effectiveness
References:
- Chaudhuri, S., & Narasayya, V. (2017). An overview of modern indexing techniques. Communications of the ACM, 60(2), 82-92.
- Stonebraker, M. (2013). The case for RAM clouds. Communications of the ACM, 56(9), 82-90.
- Tari, A., & Rastogi, R. (2017). A comprehensive survey of cloud database management systems. ACM Computing Surveys (CSUR), 50(1), 6.
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| Journal of Advanced Database Management & Systems |