During the initial stages of my group’s project, I’ve taken on the task of designing our database structure. In a couple of recent courses I’ve done some back-end development to store some entities in a data warehouse. However, I haven’t had to put together the details so specifically in an ERD or schema since the databases course. Over the past week I’ve spent a lot of time reviewing database concepts, but all that review didn’t prepare me for something I haven’t had to do yet: make actual decisions about the type of database to be used and the framework used to make it.
The differences between NoSQL and SQL were certainly covered in the databases class, but I don’t think the decision had been left to us for that class’s project. It’s been interesting to be faced with options and delve into some of the reasons to choose a particular framework, hosting service, etc. Don’t worry, I won’t bore you with an exhaustive list of all of the pros and cons of these choices. As a novice programmer, I find these kinds of decisions to be the most obviously challenging part of the profession. Sure, almost anyone can learn how to implement all sorts of data structures in a variety of languages, but knowing exactly when to utilize each of them is the hard part.
I felt fairly lost reading through descriptions of various DBMS. The scale of my group’s capstone project is fairly small, so a less-optimal choice for a DBMS would likely not set us back too far. However, I think we made the correct choice to use a SQL database and PostgreSQL as our DBMS. Our data model is almost guaranteed to stay fixed after the initial schema is set, the data is not hierarchical, and we’ll likely need to perform some complicated queries on the data [1]. Even if PostgreSQL isn’t perfect, it’s a DBMS that I haven’t used, so I’ll be eager for the chance to see something new (that will certainly be acceptable for our project).
References
[1] B. Anderson, B. Nicholson, SQL vs. NoSQL Databases: What’s the Difference?, IBM, 2022.
