Level 3: The Data Layer
Where state lives: databases, replication, partitioning, and data modeling for scale.
Welcome to Level 3
The hardest problems in system design are data problems. Choosing the right database, designing schemas for scale, understanding replication and partitioning — these decisions shape everything downstream.
What you will learn
| Module | Topic | Core Idea |
|---|---|---|
| 3.1 | Relational Databases | ACID properties, indexes, query optimization, and connection pooling |
| 3.2 | NoSQL Taxonomy | Document, key-value, wide-column, and graph — when to use each |
| 3.3 | Replication | Leader-follower, multi-leader, and leaderless strategies |
| 3.4 | Partitioning and Sharding | Range vs hash partitioning, shard key selection |
| 3.5 | Indexing Strategies | B-tree vs LSM-tree, secondary indexes, full-text search |
| 3.6 | Data Modeling for Scale | Denormalization, materialized views, access-pattern-driven design |
| 3.7 | Polyglot Persistence | Using the right database for each job in one system |
| 3.8 | Checkpoint | Design the data layer for a social media platform |
Key Takeaway
Data decisions are the hardest to change later. Understanding the spectrum from relational to NoSQL, the tradeoffs of replication strategies, and how to model data for your access patterns is the foundation of every good system design.
Connect
Start with Module 3.1: Relational Databases. Even in a NoSQL world, understanding ACID properties and indexes is essential — most systems still use a relational database for their most critical data.