Your database design determines what your application can do and how fast it can do it. Get it right early, because restructuring a production database is one of the most expensive changes you can make.
Start With the Domain
Before drawing entity-relationship diagrams, understand the business domain. What are the core entities? How do they relate? What questions will the application need to answer? The best database designs reflect the business reality, not the developer’s technical preferences.
Normalisation: The Foundation
Normalise your data to Third Normal Form (3NF) as a starting point. This eliminates data redundancy and ensures data integrity. Each fact is stored once. Updates happen in one place. Inconsistencies become structurally impossible.
Strategic Denormalisation
Pure normalisation optimises for write consistency. Real applications also need read performance. Denormalise selectively where query performance demands it — store computed values, duplicate frequently accessed data, and create summary tables for expensive aggregations.
The key is being intentional about it. Every denormalisation is a trade-off: faster reads in exchange for more complex writes and potential inconsistency. Document these trade-offs so future developers understand the reasoning.
Indexing Strategy
Indexes are the single most impactful performance tool. Index columns used in WHERE clauses, JOIN conditions, and ORDER BY statements. Composite indexes should follow the left-prefix rule — the order of columns matters.
But indexes aren’t free. Each index slows down writes and consumes storage. Index what you query, and query what you index. Use EXPLAIN to verify your queries actually use the indexes you’ve created.
Choosing Between MySQL and PostgreSQL
Both are excellent relational databases. MySQL is simpler to operate and performs well for straightforward workloads. PostgreSQL offers more advanced features: better JSON support, more sophisticated indexing (GIN, GiST), full-text search, and advanced data types.
Handling Scale
Vertical scaling (bigger server) handles more load than most people expect. Before reaching for complex distributed architectures, optimise queries, add appropriate indexes, implement caching, and consider read replicas.
When you do need to scale horizontally, consider read replicas for read-heavy workloads, table partitioning for large tables, and caching layers (Redis) for frequently accessed data. Sharding is a last resort — it adds enormous complexity.
Migration Discipline
Use migration tools (like Laravel’s migrations) for every schema change. Never modify production databases manually. Migrations provide a version-controlled history of your database’s evolution and ensure consistent schemas across environments.
The Long View
Design your database for the application you’ll have in two years, not just today. This doesn’t mean over-engineering — it means choosing flexible data types, naming conventions that scale, and relationships that can accommodate growth without restructuring.