How to choose a database for a new SaaS product

The honest answer to “which database should I use” is almost always “it depends” — which is unhelpful on its own, so here’s what it actually depends on.

Start with the workload, not the technology

Before comparing products, answer three questions about the data itself:

Is the data primarily relational? Users, organisations, subscriptions, permissions — most SaaS core data has real relationships and benefits from a schema that enforces them. This is where a relational database (Postgres, MySQL) usually wins over a document store, even though document stores are often reached for by default.

What’s the read/write ratio, and at what shape? A platform that’s read-heavy with predictable query patterns has very different needs from one with bursty writes or highly variable access patterns. Guessing wrong here is usually fixable later — but it’s expensive to fix under load.

How strict does consistency need to be? Billing and permissions data usually needs strong consistency. Activity feeds, analytics, and non-critical logs often don’t. Mixing these into a single database with a single consistency model isn’t wrong, but it’s worth being deliberate about, rather than accidental.

A reasonable default

For most new SaaS products, a managed Postgres instance is a sensible starting point: it’s relational, it handles the vast majority of realistic workloads well, and it has a mature ecosystem for extensions (full-text search, JSON columns, time-series data) that cover a lot of ground before a second, specialised database is genuinely justified.

When a second data store earns its place

Reach for something else when you have a specific, measured reason — not a hunch:

• A search experience that a relational database genuinely can’t serve well at the latency you need.
• A caching layer for data that’s expensive to compute and cheap to briefly serve stale.
• A queue or event log for asynchronous processing that shouldn’t live in the primary transactional database.

Each of these adds operational surface area: another thing to back up, monitor, patch and understand under incident pressure. That cost is often worth paying — but it should be a decision, not a default.

The mistake to avoid

The most common mistake isn’t picking the “wrong” database technically — most mainstream options can handle most SaaS workloads perfectly well. It’s picking a second or third data store before there’s a measured reason to, and inheriting the operational complexity of all of them at once.