Comparing Relational Databases to Spreadsheets. What would be the strengths and weaknesses of building a database application using a relational database vs. using a spreadsheet? Comparing Relational Databases to Spreadsheets Comparing Relational Databases to Spreadsheets Where possible, give one or more concrete examples of “use cases” that show specific strengths or weaknesses of one approach over the other

Both relational databases and spreadsheets are tools used for data management. However, they differ in functionality. For example, databases provide data types and formats that facilitate control of how to store data (Emerson, 2020). Databases also have strong controls for data integrity. In spreadsheets, there are limitations on data format and controls for data integrity (Emerson, 2020). Therefore, an application built on spreadsheets has less security on data and limited data format as compared to an application built on a relational database. Another difference between relational databases and spreadsheets is that in a relational database, relationships can be established between database objects (Emerson, 2020). This makes data management and pulling reports easier. Databases can also hold more data as compared to spreadsheets. However, when dealing with less data, spreadsheets would be ideal (Emerson, 2020). Spreadsheets are also ideal when performing calculations because of the inbuilt functions as compared to databases. Converting data from spreadsheets to other formats is possible, unlike in databases that have limited conversion options (Emerson, 2020). The choice between a relational database and a spreadsheet would be based on the function and data size of an application. In some cases, applications could use both relational databases and spreadsheets (Bendre et al., 2015).

Examples of “Use Cases” Specific Strengths or Weaknesses of One Approach Over the Other

An application used for students’ registration in a university would use a relational database instead of a spreadsheet. This is because the data captured would be stored in database objects that would require creating relationships for reporting purposes. For example, how many students registered for a certain course for the fall semester of 2020? This information could be stored in two tables; student and course. Consequently, the tables would have a relationship for the reports to be generated. Also, students’ data in a big learning institution such as a university would be a lot to store in a spreadsheet (Emerson, 2020). A statistics collection application would be based on spreadsheets because of the inbuilt functions. The data in such an application would not be much as compared to students’ registration data (Emerson, 2020).

References

Bendre, M., Sun, B., Zhang, D., Zhou, X., Chang, K. C., & Parameswaran, A. (2015). DataSpread: Unifying Databases and Spreadsheets. Proceedings VLDB Endowment, 8(12), 2000-2003. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4756475/

Emerson, K. (2020, March 6). Spreadsheets and databases as tools for data management. Research Data Services. https://researchdata.wisc.edu/storing-data/databases/spreadsheets-and-databases-as-tools-for-data-management/