The honest default
For roughly 90% of business applications, a relational database — PostgreSQL or MySQL — is the correct answer. Reach for something else only when you have a specific, measured reason. "It scales better" is not a reason until you have scale.
Database choice attracts more ideology than almost any other technical decision. It should be boring: pick based on the shape of your data and who has to operate it.
The realistic comparison
| PostgreSQL | MySQL | MongoDB | |
|---|---|---|---|
| Data model | Relational | Relational | Documents |
| Fixed schema | Yes (flexible JSON too) | Yes | No |
| Complex queries & joins | Excellent | Good | Limited |
| Transactions | Strong | Strong | Supported, more caveats |
| JSON handling | Excellent | Adequate | Native |
| Shared hosting support | Less common | Universal | Rare |
| Operational simplicity | Good | Very good | Moderate |
| Hiring in India | Good | Very easy | Moderate |
Choose by the shape of your data
- Do records have consistent fields? Customers, orders, invoices, bookings all do. That is relational data — use PostgreSQL or MySQL.
- Do you need to relate records to each other? "Show all orders for this customer in the last quarter, with product details." Joins make this trivial in SQL and painful in a document store.
- Does correctness under concurrency matter? Money, stock, and bookings need real transactions. Relational databases have decades of hardening here.
- Is your data genuinely shapeless? Event logs, varied product specifications, or third-party payloads with unpredictable fields — document stores earn their place here.
The mistake we see most often: choosing MongoDB for data that is obviously relational, then reimplementing joins in application code. This is slower, buggier, and harder to maintain than simply using a relational database. Schema flexibility is not free — you pay for it in every query you write afterwards.
PostgreSQL or MySQL?
Both are excellent. The practical differences:
PostgreSQL when
- You want stricter data integrity by default
- You need advanced queries — window functions, CTEs
- You will store significant JSON alongside relational data
- You may need geospatial features (PostGIS)
- You control your own hosting
MySQL when
- You are on shared hosting
- You are running WordPress or similar
- Your team already knows it well
- You want the widest possible hosting compatibility
- Your queries are straightforward
Things that matter more than which database
A well-indexed MySQL database beats a badly-indexed PostgreSQL one every single time. The engine rarely determines performance — the schema and the queries do.
- Indexes on the columns you filter and join by. The most common cause of slow applications, by a wide margin.
- Avoiding N+1 queries. Fetching a list, then querying once per row, will destroy performance regardless of engine.
- Sensible schema design. Normalise until it hurts, then denormalise deliberately where measurement justifies it.
- Connection pooling. Opening a connection per request wastes far more than any engine difference.
- Backups that have been restored at least once.
When specialised databases genuinely help
| Need | Tool | Note |
|---|---|---|
| Caching, sessions, queues | Redis | Alongside your main DB, not instead of it |
| Full-text search at scale | Elasticsearch / Meilisearch | Postgres full-text is enough for most |
| Time-series / metrics | TimescaleDB, InfluxDB | Only at genuine volume |
| Analytics over billions of rows | ClickHouse | Separate from your transactional DB |
| Embedded / offline | SQLite | Excellent and underrated |
SQLite deserves more credit. For desktop applications, mobile apps, and even modest web applications, it is fast, zero-administration, and stores everything in one file. Many projects that reach for a database server would be simpler and faster on SQLite.
A practical recommendation
Starting a new business application with no unusual constraints: PostgreSQL. It is capable, strict where strictness helps, handles JSON well when you need flexibility, and you are unlikely to outgrow it.
On shared hosting or building on WordPress: MySQL, without hesitation.
Add Redis when you have measured a caching need. Add anything else only when you can name the specific problem it solves.
Designing a system and unsure about the data layer? Describe your data. See also our custom database engine service for cases where standard engines genuinely do not fit.