Autonomous Databases and Artificial Intelligence: Architectures, Optimization, and Governance

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Authors

Shashipurna Kurapati
Artificial Intelligence, Data Management
https://orcid.org/0009-0005-5159-0252

Keywords:

Artificial Intelligence, Machine Learning, Big Data, Cloud Computing, Vector Database, Graph Database, Data Governance

Synopsis

Artificial Intelligence-native databases are currently at the forefront of the rapidly evolving data management landscape. The book examines how database systems are changing to satisfy the needs of real-time, intelligent decision-making in different industries. The transition from traditional relational models to AI-driven architectures, cloud integration, optimization, and new developments like automation, explainability, and security are all covered in the chapters.

This book's writing has involved both a thorough examination of contemporary data technology and a contemplation of the field's continuing opportunities and challenges. I want professionals, students, and anybody else interested in the future of databases to be able to understand both basic and advanced topics. I hope it encourages readers to welcome innovation and investigate the wise opportunities that lie ahead.

I want to express my gratitude to my parents for their unwavering support during my journey, as well as to my peers, fellow researchers, and everyone else who has helped and inspired me. Their guidance and collaboration have been invaluable in shaping this book.

References

Gadde H. AI-Augmented Database Management Systems for Real-Time Data Analytics. Revista de Inteligencia Artificial en Medicina. 2024;15(1):616-49.

Ojika FU, Owobu O, Abieba OA, Esan OJ, Daraojimba AI, Ubamadu BC. A conceptual framework for AI-driven digital transformation: Leveraging NLP and machine learning for enhanced data flow in retail operations. IRE Journals. 2021 Mar;4(9).

Muppala, M. . (2025). Digital Oceans: Artificial Intelligence, IoT, and Sensor Technologies for Marine Monitoring and Climate Resilience. Deep Science Publishing. 2025; doi:10.70593/978-93-7185-787-1

Koneti SB. Artificial Intelligence-Powered Finance Algorithms, Analytics, and Automation for the Next Financial Revolution. Deep Science. 2025; doi:10.70593/978-93-7185-613-3

Eboigbe EO, Farayola OA, Olatoye FO, Nnabugwu OC, Daraojimba C. Business intelligence transformation through AI and data analytics. Engineering Science & Technology Journal. 2023 Nov 29;4(5):285-307.

Downloads

Full Text Book

Published

3 October 2025
Copyright (c) 2025 Shashipurna Kurapati

Details about the available publication format: E-Book

E-Book

ISBN-13 (15)

978-93-7185-652-2

Details about the available publication format: Book (Paperback)

Book (Paperback)

ISBN-13 (15)

978-93-7185-667-6

How to Cite

Kurapati, S. . (2025). Autonomous Databases and Artificial Intelligence: Architectures, Optimization, and Governance. Deep Science Publishing. https://doi.org/10.70593/978-93-7185-652-2
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