Choosing the right database is one of the most important architectural decisions you'll make. The wrong choice can lead to performance issues, scaling problems, and unnecessary complexity. Here's how to choose wisely.
SQL vs NoSQL: Understanding the Difference
SQL databases (PostgreSQL, MySQL) are relational:
- Structured data with defined schemas
- Strong relationships between data
- ACID compliance for data integrity
- Excellent for complex queries
NoSQL databases (MongoDB, DynamoDB) are flexible:
- Schema-less or flexible schemas
- Designed for specific use cases
- Often easier to scale horizontally
- Great for unstructured or rapidly changing data
The choice isn't about which is 'better'—it's about which fits your needs.
When to Choose SQL Databases
SQL databases excel when you have:
- Structured, relational data (users, orders, products)
- Need for complex queries and joins
- Requirements for data integrity and consistency
- Financial or transactional data
- Well-defined data models
Most business applications benefit from SQL databases. They've been refined for decades and handle the majority of use cases excellently.
Popular choices: PostgreSQL (our default), MySQL, SQLite.
When to Choose NoSQL Databases
NoSQL makes sense for:
- Highly dynamic or unstructured data
- Massive scale requirements
- Real-time features (chat, live updates)
- Document storage (CMS, catalogs)
- Time-series data (analytics, monitoring)
NoSQL isn't a silver bullet. Many projects that start with NoSQL later wish they'd used SQL.
Popular choices: MongoDB (documents), Redis (caching), Firebase (real-time).
Cloud vs Self-Hosted
Cloud-managed databases (RDS, Supabase, PlanetScale):
- Automated backups and updates
- Easy scaling
- Higher cost but lower maintenance
- Great for most modern applications
Self-hosted databases:
- More control and customization
- Lower ongoing costs at scale
- You handle all maintenance
- Requires more DevOps expertise
For most businesses, cloud-managed databases are the right choice. The operational overhead of self-hosting rarely justifies the cost savings.
Data Size and Scale Considerations
Be realistic about scale:
- Most applications start small
- Premature optimization is wasteful
- Modern databases handle millions of rows easily
- You can migrate later if needed
Don't choose a complex distributed database 'just in case.' Start simple, measure performance, and scale when you actually need to.
A well-optimized PostgreSQL database can handle far more than most people realize.
Making Your Decision
Ask yourself:
1. What does my data look like? (structured vs unstructured)
2. What are my consistency requirements?
3. What queries will I run most often?
4. What's my expected scale in the next 2 years?
5. What's my team's experience level?
When in doubt, start with PostgreSQL. It's powerful, reliable, and handles most use cases excellently. You can always add specialized databases later for specific needs.
Database selection doesn't have to be overwhelming. For most business applications, a well-configured SQL database like PostgreSQL is the right choice. Start there, optimize as you grow, and add specialized databases only when you have a specific need that justifies the added complexity.