ARTIFICIAL INTELLIGENCE APPROACHES IN DATABASE MANAGEMENT SYSTEMS

Krassimira Shvertner ()
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Krassimira Shvertner: Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski

Yearbook of the Faculty of Economics and Business Administration, Sofia University, 2020, vol. 18, issue 1, 303-326

Abstract: The growth of data volumes and the need for fast analytical data processing lead to significant efforts to answer effectively these major challenges. Data processing plays key role and is the leading motivation for the research and development in software and hardware technologies. Now there are new trends in databases technologies: the integration of Artificial Intelligence (AI) and Database Management System (DBMS) technologies promises to play a significant role in shaping the future of computing. AI/DB integration is crucial not only for next generation computing but also for the continued development of DBMS technology. Both DBMS and AI systems represent well established technologies, research and development in the area of AI/DB integration is comparatively new. The motivations driving the integration of these two technologies include the need for access to large amounts of shared data for data processing, efficient management of data, and intelligent processing of data. Information Technology (IT) industry is introducing autonomous hardware and the first autonomous databases. The expectation is that using methods of the machine learning and sophisticated program algorithms most of the maintenance activities will be automatically done. The in-memory functionality leads to new approaches in the data processing algorithms and database architecture. The paper observes also big improvements in the hardware and software of complex engineered database machines (Exadata, Exalytics) and new database, which was designed and successfully implemented in Europe by the SAP HANA.

Keywords: In-memory Data Bases; Analytical Data Processing; Engineered Database Appliances; Exadata; Autonomous Databases; Oracle 18c. (search for similar items in EconPapers)
Date: 2020
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