Summary
In this episode, we cover the fundamentals of relational databases, explaining how they store structured data in tables with rows and columns. We explore primary keys for unique identification, foreign keys for connecting tables, and the different types of relationships like one-to-one, one-to-many, and many-to-many. We also discuss normalization for organizing data efficiently and introduce SQL as the language used to define, insert, and query data across related tables.
Transcript
Let's start with the basics. A relational database stores structured data and models how things relate to each other. Think of users, posts, comments—all separate tables that get connected through keys. Tables are the foundation. Each table represents a type of thing in the system, like a user, an order, or a product. Each row is a single record, where each column in that row is a property or field of that record. So just like a spreadsheet, you have simple, structured, and consistent data. Now each table needs a way to uniquely identify a row, and that's where primary keys come into the picture. This is often an ID field—just an auto-incrementing integer, so we have one, two, three, four, five, where each number will uniquely identify a row. So even if we have two users with the same names, their IDs make them unique. Relational databases really shine when you have data that is relational to each other. For example, if we have a users table and a posts table, those two are connected or relational to each other. The way we can connect them is to use what is known as foreign keys—where one table references another table. This lets us answer questions like "show me all posts by Alice." Now relationships come in a few forms depending on how the data is connected. Choosing the right relationship is key to a clean database schema or design. We can have one-to-one, one-to-many, or many-to-many. For example, with our data we can have one-to-many—like a user can have many posts, but a post can only have one user. This concept is known as normalization, and it's about organizing data for consistency. You break data into smaller related tables and then reference them instead of duplicating the information in one table. This creates a more manageable database that is easier to reason about. Now SQL is the language of relational databases. It's how we define tables, how we insert data, and query data across relationships. As you can see here, we have an SQL query where we select the username and post title from the users and posts tables, and then we simply use a JOIN statement to put them together so that we can actually connect the tables through the foreign key.