Intermediate10 min readPerformance & Scaling
Denormalization
Deliberately duplicating database records to eliminate slow SQL JOIN operations during reads.
What you'll learn
- Normalization (up to 3NF)
- Denormalization
TL;DR
Deliberately duplicating database records to eliminate slow SQL JOIN operations during reads.
Concept Overview
Normalization vs. Denormalization is a core database schema design decision. Normalization decomposes tables to eliminate duplicate records, while Denormalization deliberately duplicates data to speed up complex read queries by eliminating joins.
Key Architectural Pillars
1
Normalization (up to 3NF)
Organizing database schemas to ensure each data fact is stored exactly once, ensuring maximum write integrity.
2
Denormalization
Duplicating columns across multiple tables to optimize read performance and bypass expensive JOIN queries.
More in this module
Cache Fundamentals
Storing frequently accessed lookup results in memory blocks (RAM) to bypass slow disks.
Cache Patterns
Comparing Cache-Aside, Read-Through, Write-Through, and Write-Back data synchronization models.
Cache Invalidation
Keeping cache blocks accurate during system updates (Purge, TTL, Write-Through).