Why my Imagined Workplace Should Move From a Traditional RDBMS to a NoSQL Database
Discussion
My imagined workplace should move from a traditional RDBMS to a NoSql database to enjoy several features; in the end, the organization will enjoy an improvement in the work experience and the overall success in the various database management tasks. The preference will be based on the relevance with the advances and efficiencies that employees will be experiencing in the course.
NoSQL database will help the organization to solve the challenges that have long been experienced with the use of a relational database. According to Clark (2014), the use of the given form of databases will be significantly important for the organization to fit in the contemporary society especially with the increasing amount of data that needs to be stored for efficient and effective access in the working environment. Moreover, they are also used to manage distributed data stored and accessed remotely to ensure smooth operation in the organization. The ease of handling heterogeneous data, while experiencing horizontal scaling, and parallel processing concerning massive data makes NoSQL databases preferred for connecting with several servers (Kabakus & Kara, 2017). There have been considerable changes recorded on the data storage following the evolution brought by the concept of cloud computing and big data. The emerging needs involve aspects like the exponential data growth demanding new storage infrastructure; this is relevant to the features that are guaranteed by the use of NoSQL databases.
The wide acceptance of the alternative form of the database can be traced with the significant challenges that the concept of big data introduced around data capture and storage. It is important to note the relational databases are not sufficient to handle big data due to associated difficulties. This is because working with relational databases requires considerable effort for accommodating the requirements for storing big data (Ramos et al., 2020). This is however efficiently solved as long as the NoSql database is adopted and used.
Moreover, current projects involve the installation of cloud applications which calls for storage systems which can assure high performance and scalable system. On this note, NoSql has been proven to be successful in projects and exercises involving the need for handling the huge growth of such unstructured and semi-structured data. Schulz et al. (2016) argued that it is therefore preferred because of the capability of supporting the database research community which is focused on the establishment of distributed and scalable solutions to manage the large volumes of data. Farias et al. (2014) observed that researchers have confirmed that NoSQL has fast emerged to be a proper revolutionary solution that currently guarantees data replicating, horizontal scaling, and partitioning to ensure that the associated services run across servers. In the end, the exercises in which it is implemented meet the standards that have been approved by the operation of the current application. This is important to achieve the efficiencies expected of the many simple operations taking place per unit time.
Further use of NoSQL for storage purposes in a working environment include the support it guarantees for the various activities like Online Transaction Processing, ETL data transformation style, predictive and exploratory analytics. Each NoSQL database is useful for storage purposes accomplished in a specialized format based on the needs derived from the current applications. NoSQL databases show essential availability and scalability made possible through the Key-Value Store databases; it ensures that that availability is assured for almost 100% (Clark, 2014). The dynamic addition of records is also possible with this form of a database making it one of the most preferred forms of the NoSql database.
Moreover, the workplace operates on content and metadata store; this is important because the organization needs an unlimited repository for the storage of a large amount of data, which exist in many forms. According to Farias et al. (2018), this will be important in ensuring that the organization gains the adequate capability of merging the various learning tools and using them from a single platform. Handling such applications which could also be content-based, is dependent on the frequent access of metadata, and for which less response time is needed. While the organization needs content-based applications, the use of NoSQL becomes crucial for the assurance of flexible and fast access to, and storage of data in various content types.
The organization also needs to handle data around mobile applications. This is meant to cater for the needs of all the users as far as data management is concerned. The number of Smartphone users has recorded a significant increase, which is rapidly manifested in terms of solutions established toward the challenges that mobile applications face regarding growth and volume (Clark, 2014). The organization will need to use the NoSQL database for the development of mobile applications; the project on the same can be accomplished from a relatively small size, which can easily be expanded considering the increase in the number of users. This cannot be undertaken if the organization would rather consider and implement relational databases.
Finally, the organization embraces the aggregation of data which extends to the services affecting even the third party users. On the same note, the organization looks forward to experiencing frequent access to the data generated by the third party. Kabakus and Kara (2017) present a probable phenomenon that may occur as the need to record sales and purchase data to keep for future reference. In such a scenario, the suitability of the NoSQL databases is evaluated based on the possibility of the management of huge amounts of data which is frequently experienced.
References
Clark, L. (2014). Using NoSQL Databases To Gain Competitive Advantage. Computer Weekly, 17-19. Retrieved 11 June 2020, from https://eds-a-ebscohost-com.ezproxy.umgc.edu/eds/detail/detail?vid=0&sid=0ab16010-c093-4b12-abe3-6b45a41c02b6%40sdc-v-sessmgr03&bdata=JnNpdGU9ZWRzLWxpdmUmc2NvcGU9c2l0ZQ%3d%3d#AN=96120875&db=f5h.
Farias, V., Sousa, F., Maia, J., Gomes, J., & Machado, J. (2018). Regression-based performance modelling and provisioning for NoSQL cloud databases. Future Generation Computer Systems, 79, 72-81. https://doi.org/10.1016/j.future.2017.08.061
Kabakus, A., & Kara, R. (2017). Performance evaluation of in-memory databases. Journal Of King Saud University – Computer And Information Sciences, 29(4), 520-525. https://doi.org/10.1016/j.jksuci.2016.06.007
Ramos, M., Sánchez-de-Madariaga, R., Barros, J., Carrajo, L., Vázquez, G., & Pérez, S. et al. (2020). An Archetype Query Language interpreter into MongoDB: Managing NoSQL standardized Electronic Health Record extracts systems. Journal Of Biomedical Informatics, 101, 103339. https://doi.org/10.1016/j.jbi.2019.103339
Schulz, W., Nelson, B., Felker, D., Durant, T., & Torres, R. (2016). Evaluation of relational and NoSQL database architectures to manage genomic annotations. Journal Of Biomedical Informatics, 64, 288-295. https://doi.org/10.1016/j.jbi.2016.10.015