Version 1
: Received: 18 April 2024 / Approved: 19 April 2024 / Online: 22 April 2024 (08:38:10 CEST)
How to cite:
Altaher, R. Transparency Levels in Distributed Database Management System DDBMS. Preprints2024, 2024041327. https://doi.org/10.20944/preprints202404.1327.v1
Altaher, R. Transparency Levels in Distributed Database Management System DDBMS. Preprints 2024, 2024041327. https://doi.org/10.20944/preprints202404.1327.v1
Altaher, R. Transparency Levels in Distributed Database Management System DDBMS. Preprints2024, 2024041327. https://doi.org/10.20944/preprints202404.1327.v1
APA Style
Altaher, R. (2024). Transparency Levels in Distributed Database Management System DDBMS. Preprints. https://doi.org/10.20944/preprints202404.1327.v1
Chicago/Turabian Style
Altaher, R. 2024 "Transparency Levels in Distributed Database Management System DDBMS" Preprints. https://doi.org/10.20944/preprints202404.1327.v1
Abstract
This review study explores and analyzes distributed database management systems (DDBMS), focusing on the important role of transparency methods in improving the functioning and interaction between users and systems. Transparency in DDBMS refers to several important factors, such as data, replication, performance, scaling, and network transparency. Each one of these components plays a role in concealing the intricate operations that underlie distributed systems from the end user. This not only speeds interactions but also enhances the reliability of the system. The article highlights the criticality of data independence as well as replication transparency in particular. Data independence enables adaptable modifications to the system's architecture and alterations to be made without causing any disruption to user activities. On the other hand, replication transparency ensures that the data remains consistently accurate across distributed nodes, even in the absence of user awareness. Moreover, the article investigates the progression of DDBMS through the incorporation of cutting-edge technologies such as quantum computation and artificial intelligence, which are anticipated to significantly augment the capabilities of data processing. The text proposes potential avenues for further investigation, emphasizing how these advancements may enhance the fundamental resilience of database management systems (DBMS) and expand their applicability in intricate, data-rich settings.
Keywords
DDBMS; Transparency; data independence; Replication Transparency
Subject
Computer Science and Mathematics, Data Structures, Algorithms and Complexity
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
