Almost every backend needs somewhere to persistently store data, and the relational database — data organized into rows and columns across related tables — is still the default choice for most applications. This module covers how relational databases think about data, and the language you use to talk to them: SQL.
You'll look at why tables get split apart through normalization instead of dumping everything into one giant table, how primary and foreign keys link related rows together, and how joins let you pull that related data back out in a single query. The module wraps up with PostgreSQL, one of the most widely used relational databases in production today.
With tables, keys, and queries under your belt, you'll be ready to connect a database to real endpoints in Building APIs, the next module in this course.
An introduction to how relational databases organize data into rows and columns, and why that structure has stayed the default for decades.
A rapid-fire tour of SQL: selecting, filtering, and inserting data, and the handful of keywords that cover most day-to-day queries.
Why data gets split across multiple related tables instead of one big table, and how the normal forms guide that process step by step.
How a primary key uniquely identifies a row, and how a foreign key constraint links that row to related data in another table.
Inner, left, right, full, cross, and self joins — how each one combines rows from multiple tables, and when to reach for which.
A quick look at Postgres, one of the most popular open-source relational databases, and what sets it apart from the rest.