How Storage Actually Works

There are three fundamental ways to store data, and they map to three fundamental data structures you already know from school. Arrays — ordered sequences, indexed by position. Dictionaries — key-value pairs, named access. Trees and graphs — relationship-based, for connected data like social networks. Every storage system you will encounter in production is built on one of these three primitives. The question is which one to reach for and why. This lecture draws the line clearly. If you need to find something by position, you use an array-based structure. If you need to find it by name or ID, you use a dictionary. If you need to traverse relationships — who follows whom, what belongs to what — you need a tree or graph. The storage building blocks in the 7 building blocks framework (Key-Value Store, File Store, Relational Database) are each rooted in one of these three. What You'll Learn: - Arrays as storage — ordered, indexed by position, what that enables and what it does not - Dictionaries as storage — key-value access, named lookup, why this is so common in production systems - Trees and graphs as storage — relationship traversal, when structure matters more than speed - How these three primitives become real building blocks — Key-Value Store, File Store, Relational Database - The question that picks the right storage — what type of access do you actually need? Why This Matters: - Defaulting to a relational database for everything is one of the most common and avoidable system design mistakes - The ability to match access patterns to storage types is what separates architectural thinking from guesswork - Every system you will ever build uses at least one of these three — knowing which one and why is the skill This lecture is the storage foundation for the 7 building blocks framework. The full framework — with labs and challenges — is in Course I at systemthinkinglab.ai. Course I → https://systemthinkinglab.ai/course-1 Free interactive challenges → https://systemthinkinglab.ai/learn