Tech Research Paper: Database Types

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We present you an example of Technology Research Papers, “Cloud Database and Traditional Database,” written by our expert writers.

Cloud and Traditional Database

Abstract

The latest developments in technology have changed the shape of data storage. Cloud database systems have been introduced as a response to traditional relative database models. This assignment presents insights and comparisons into both database systems. Although relational systems are more favorable by small and medium-scale old-school companies, many research and statistics have shown the comparative advantage of cloud-based database systems in terms of scalability, costs, accessibility, security, and deployment.

Keywords: traditional database, relational, cloud database, cloud-based systems

Introduction

Databases, whether traditional and cloud, are broadly storages of information in an electronic environment. The type of information is often transactional. The usage of such services has been increasing in such a drastic manner that almost %95 of all data has been created in the last two years (SAP HANA, 2020). More specifically, extraordinary transfer and download speeds due to the latest development in technologies has enabled vast amounts of diverse data worldwide; however, in today’s world, there are now multiple options for managing such a big data thanks to cloud data warehouses and traditional databases (Al Shehri, 2013; Bhatti & Rad, 2017; Donkena & Gannamani, 2013). Although both seem to function in a similar way, they offer different solutions. In this direction, this paper will analyze cloud and traditional databases in terms of their description, differences, similarities, construction process, processes, applications, security concerns, deployment options, query speeds, and scalability. After all, although relational systems are more favorable by small and medium-scale old-school companies, many research and statistics have shown the comparative advantage of cloud-based database systems in terms of scalability, costs, accessibility, security, and deployment.


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Figure 1. The general structure of Traditional Databases (Jain & Alam, 2017).

Broadly, a database is considered storage for information. This kind of information is generally transactional and electronically kept in databases. In this sense, companies and vast organizations tend to have a lot of traditional databases, in which the information is stored from a mere operational system.

Also, a relational system is used to organize the information in a traditional database. In this way, information is stored in tables, rows, and columns. In such a database, “the information is continuously updated, modified, deleted, and added in the technical database catalog” (SAP HANA, 2020, n.p.). Also, such traditional databases generally do not offer a visual-graphical interface to present the data. In other words, a user should be competent in comprehending a query language in order to excel at a traditional database, and SQL is one of those languages in a way (Norris, 2017). After all, one may readily highlight that a user should be highly trained in order to make use of the data available in traditional databases in a meticulous and decent manner. In other words, a qualified database administrator or database specialist is required to maintain the sustainability and operations of the dataset.

Cloud Database

Similar to traditional databases, cloud databases are also concentrated on data storage. The biggest difference from the traditional one is end-to-end analytics. In other words, cloud databases allow users to make use of data from multiple sources, which makes the data available across a wide spectrum of different users. Also, the data may come from social media channels or e-trade platforms. Regardless of the source of the data, cloud databases provide fast querying across multiple data sources as the data is stored in cloud-single storage.


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Figure 1. Relational Cloud Architecture (Jain & Alam, 2017).

Furthermore, the real difference is the “translation capabilities, these make it possible for any user to navigate through the data, and SAP Data Warehouse Cloud’s semantic layer translates raw data into the business language to allow organization users to fully comprehend the various sets of tables and views” (SAP HANA, 2020, para. 6). More specifically, regardless of the position of the user, whether analysts or data scientists, data is translated into knowledge, and this aspect makes it possible for users to make use of the collected data.

Advantages and Disadvantages of Different Database Systems

Transitioning from traditional database formation to a complete cloud infrastructure provides a lot of benefits for companies and organizations. Overall cost, mobile access, flexible solutions, disaster recovery, and security are among the leading benefits of cloud-based database systems (Marina et al., 2016). More specifically, expanding the current in-site database to have more storage is costly when compared to cloud systems. However, in cloud-based systems, the cost will merely go up when the organization wants to expand its digital storage or demand additional consultancy services. Also, cloud database systems provide flexible solutions to businesses in terms of managing data. That is, there are no inherent restrictions with cloud systems, and as these systems are drastically improved by data scientists, the organization does not need to invest a lot of money in the sustainability of physical storage capabilities. Simply, an agreement or subscription to such a cloud system will be sustainable, efficient, and flexible for the company.

Figure 2. Traditional vs. Cloud Data Services (Jain & Alam, 2017).


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Cloud-based database services also provide mobility. As the business grows, mobile teams will not have any problems regarding accessing the organizational data as they are available at any moment. When compared to prototype on-site traditional database servers, the disaster recovery of cloud services is relatively effective, fast, and responsive. In other words, it will not take weeks to restore data out of a disaster with cloud database systems.

On the other hand, cost concerns, system vulnerabilities, vendor lock-in, and connection downtime can be considered among the negative aspects of cloud-based systems. More specifically, it would be harder for an organization to change its cloud database vendor as the process of transfer from one provider to another is often complicated. Also, with the wrong cloud plan, an organization may pay lots of money to cloud systems. In other words, a meticulous projection is required to evaluate the required data storage capability in order not for organizations to pay sharp amounts of money when compared to traditional database services.

Although cloud systems are highly protected, no system is infinitely safe. Therefore, they can be attacked or even hacked electronically; risks can be quite mitigated by keeping up with the security concerns and recommendations of the cloud base specialists. Also, as these cloud database systems are highly dependent on the internet service providers, there can be problems regarding the internet connection when compared to traditional database services.

Applications of Databases

Microsoft SQL AZURE, Amazon Relational Database Service (Amazon RDS), Google Cloud SQL, Google Datastore, and Database.com are among the leading applications for cloud-based systems (Curino et al., 2013). On the other hand, traditional systems require a setup, and they tend to have local systems, unlike the aforementioned applications. They may as well make use of SQL systems. However, they are not internet-based.

Oracle, MySQL, Teradata, MariaDB, Microsoft Access, SQLite, IBM DB2, PostgreSQL, and Apache Hive are among the leading applications of traditional relational database systems.


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Figure 3. Common Security Consideration Relative Cloud (Shehri, 2013)

Scalability of Databases

Relative databases are now antique when compared to cloud solutions as their storage capacity is quite dependent on the preferences of the users. Within seconds, the storage capacity of cloud systems can be increased. However, this approach is not possible in relative traditional databases as they require sophisticated and meticulous internal setup procedures on LAN. More specifically, expanding storage capacity on cloud-based systems will not be a physical, locational problem for an organization as they are handled by platforms through quick arrangements and agreements.

Traditional databases require more time and effort in terms of location, expansion, and deployment time, as they need a provisional testing period for the new storage capacity. Also, extra IT specialists may be required if storage capacity is drastically increased to manage the data accordingly. In this sense, the overall scalability of cloud systems seems way more advantageous and cost-friendly for vast organizations in the long run.

Conclusion

As a result, this paper has analyzed cloud and traditional databases in terms of their description, differences, similarities, construction process, processes, applications, security concerns, deployment options, query speeds, and scalability. Accordingly, similar to traditional databases, cloud databases are also concentrated on data storage. The biggest difference from the traditional one is end-to-end analytics. In other words, cloud databases allow users to make use of data from multiple sources, which makes the data available across a wide spectrum of different users. Transitioning from traditional database formation to a complete cloud infrastructure provides a lot of benefits for companies and organizations. Overall cost, mobile access, flexible solutions, disaster recovery, and security are among the leading benefits of cloud-based database systems. After all, although relational systems are more favorable by small and medium-scale old-school companies, many research and statistics have shown the comparative advantage of cloud-based database systems in terms of scalability, costs, accessibility, security, and deployment.

References

Al Shehri, W. (2013). Cloud database as a service. International Journal of Database Management Systems, 5(2), 1–12. Retrieved November 23, 2020, from https://doi.org/10.5121/ijdms.2013.5201

Bhatti, H., & Rad, B. (2017). Databases in cloud computing: A literature review. International Journal of Information Technology and Computer Science, 9(4), 9–17. Retrieved November 23, 2020, from https://doi.org/10.5815/ijitcs.2017.04.02

Curino, C., Jones, E., Popa, R. A., Malviya, N., Wu, E., Madden, S., Balakrishnan, H., & Zeldovich, N. (2013). Relational Cloud: A Database-as-a-Service for the Cloud [PDF]

Donkena, K., & Gannamani, S. (2013). Performance evaluation of a cloud database and traditional database in terms of response time while retrieving the data [PDF]. diva-portal.org.

Jain, S., & Alam, M. (2017). Comparative Study of Traditional Database and Cloud Computing Database. International Journal of Advanced Research in Computer Science.

Marina, B., Memon, D., & Naz, R. (2016). Comparative analysis of Cloud database, remote database, and traditional database. International Journal of Computer Science and Information Security, 14(10), 242–246.

Norris, D. (2017, October 2). DBaaS vs Traditional Databases: Why You Should Pay Closer Attention. stratoscale.com.

SAP HANA. (2020, April 9). What’s the difference between a database and cloud data warehouse? SAP HANA Journey.

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