| Issue |
E3S Web Conf.
Volume 412, 2023
International Conference on Innovation in Modern Applied Science, Environment, Energy and Earth Studies (ICIES’11 2023)
|
|
|---|---|---|
| Article Number | 01108 | |
| Number of page(s) | 9 | |
| DOI | https://doi.org/10.1051/e3sconf/202341201108 | |
| Published online | 25 August 2023 | |
Creation of column-oriented NoSQL databases automatically in Big Data environments and its impact on energy consumption
University Mohammad Premier, Oujda, Morocco
This study investigates the automatic creation of column-oriented NoSQL databases in Big Data environments and their impact on energy consumption. Traditional row-oriented databases face limitations in handling large volumes of data, resulting in slower query response times and energy inefficiencies. In contrast, column-oriented NoSQL databases store data in columns, enabling efficient compression, retrieval, and query processing. Innovative techniques are employed to automatically create these databases, optimizing performance and minimizing manual intervention. Storing data in a columnar format reduces storage requirements and power consumption while improving data locality and reducing I/O operations. This study emphasizes the benefits of adopting column-oriented NoSQL databases, including improved performance, scalability, and energy efficiency in Big Data environments.
Key words: Big DATA / SQL relational database / NoSQL / energy efficiency / The transformation rules / BigData / CQL
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.