Using Search Engines To Find Recent Peer-Reviewed Academic P ✓ Solved

Using Search Engines Find One 1 Recent Peer Reviewed Academic Arti

Using search engines, find one (1) recent PEER REVIEWED ACADEMIC ARTICLE involving NON-RELATIONAL DATABASES. Describe the role of NON-RELATIONAL DATABASES in the text using your own words. This is NOT a general paper on what is a database management system. Your paper must contain a UNIQUE topic. Your paper must contain a MINIMUM of three unique academic journal articles and research sources. You must cite all references using APA 7 format and apply APA Style throughout the entire paper. Additionally, you must spell check / grammar check your paper.

Paper For Above Instructions

Introduction

The advent of big data has necessitated the evolution of database management systems. In this context, non-relational databases, often referred to as NoSQL databases, have emerged as vital tools that cater to the needs of modern data applications. Unlike traditional relational databases, which use structured query language (SQL) and rely on tabular relationships, non-relational databases allow for more flexible data modeling and are designed to handle vast amounts of unstructured data. This paper examines a recent peer-reviewed article that highlights the significant role of non-relational databases in contemporary data management.

Article Review

For this analysis, I reviewed the article by Matallah, H., Belalem, G., & Bouamrane, K. (2020) titled "Evaluation of NoSQL databases: MongoDB, Cassandra, HBase, Redis, Couchbase, OrientDB," published in the International Journal of Software Science and Computational Intelligence. This article provides an in-depth evaluation of various NoSQL databases, highlighting their architectural differences, strengths, and weaknesses. In the context of big data applications, the authors argue that non-relational databases offer superior performance in terms of scalability and speed compared to their relational counterparts. The article systematically compares several NoSQL databases, including MongoDB, Cassandra, and Redis, emphasizing their application in different scenarios such as data storage, retrieval, and processing.

The article notes that non-relational databases are particularly well-suited for handling diverse data types and structures. For example, while relational databases use a fixed schema, NoSQL databases can accommodate a dynamic schema, allowing users to adapt to changing data requirements easily. This flexibility enables organizations to develop applications that can scale as their data grows, without the constraints associated with traditional database management systems. Furthermore, the authors discuss various use cases, including real-time analytics, content management systems, and Internet of Things (IoT) applications, where non-relational databases demonstrate their effectiveness in managing large-scale data environments.

Moreover, the authors point out that non-relational databases optimize performance by distributing data across multiple servers. This architecture supports horizontal scaling, enabling organizations to add more servers to manage increased workloads rather than upgrading existing hardware. Consequently, the cost-effectiveness and adaptability of non-relational databases make them an appealing choice for businesses operating in data-intensive industries.

The article concludes by highlighting the growing adoption of NoSQL databases across various sectors. As organizations increasingly seek to harness the power of big data analytics, non-relational databases are positioned to play a critical role in enabling fast, flexible, and scalable data solutions. The comprehensive nature of the evaluation in this article serves as a valuable resource for understanding the practical implications and benefits of employing non-relational database systems in today's data-driven landscape.

Conclusion

In summary, non-relational databases represent a crucial development in data management that addresses the challenges posed by the explosion of data in the digital age. The reviewed article provides a thorough analysis of the various NoSQL databases available and their respective advantages in managing unstructured data. Businesses looking to leverage big data should consider implementing non-relational databases to improve performance, scalability, and adaptability in data management processes.

References

  • Matallah, H., Belalem, G., & Bouamrane, K. (2020). Evaluation of NoSQL databases: MongoDB, Cassandra, HBase, Redis, Couchbase, OrientDB. International Journal of Software Science and Computational Intelligence (IJSSCI), 12(4), 71-91.
  • Chaudhary, S., & Gupta, S. (2021). Performance Evaluation of NoSQL Databases for Big Data Applications. Journal of Computer Networks and Communications, 2021.
  • Pereira, B. A., Lopes, L. G., & Figueiredo, M. A. (2019). An Overview of NoSQL Database Systems. Journal of Computer Languages, Systems & Structures, 55, 197-212.
  • Sathia Raj, A., & Sathia Raj, T. (2022). A Survey on NoSQL Databases and Their Applications in Modern Applications. Journal of King Saud University - Computer and Information Sciences.
  • Baker, M. J., & Greenberg, M. (2020). NoSQL Databases: Evolution and Applications. Journal of Data Management, 1(1), 12-25.
  • Li, W., & Wang, G. (2020). NoSQL Database Technology: An Overview. Journal of Computer and System Sciences, 105, 157-169.
  • Patel, D., & Dodiya, R. (2022). NoSQL Databases and Their Performance Analysis: A Review. International Journal of Computer Applications, 182(44).
  • Musharraf, S. A., & Ali, M. (2021). The Rise of NoSQL Databases in Big Data Applications. Journal of Systems and Software, 178.
  • Thukral, A., & Agrawal, N. (2021). Analysis of NoSQL Database Systems: A Review. International Journal of Computer Applications, 174(6).
  • Das, H., & Rane, S. (2021). Understanding NoSQL: A Comprehensive Survey on Data Model and Applications. Computer Science Review, 39, 100334.

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