SQL vs NoSQL for a small SaaS: how do I choose?

Short answer: for most small SaaS products with accounts, billing and reports, start with a relational database unless you have a specific reason not to. Both families work; the question is which failure modes you would rather have.

What to weigh

• Shape of the data. Users, organisations, plans, invoices and line items are related and need joins and totals. Relational databases model this directly, with foreign keys and constraints that catch bugs early.
• Transactions. Moving money, stock or credits across several rows needs atomic updates. Relational databases do this by default. MongoDB supports multi-document transactions on a replica set, but you must design for it from the start.
• Reporting. Ad hoc questions ("revenue by plan by month") are far easier in SQL. Aggregation pipelines can do it, but most teams find SQL easier to hand to an analyst.
• Flexible documents. If much of your data is genuinely variable (form builders, event payloads, CMS blocks), a document store, or a JSON column in a relational database, fits well.
• Team skill. The database your team can operate, back up and tune is usually the better choice.

A practical default

Use PostgreSQL or MySQL for the core, and store the variable parts in a JSON column. You get constraints where they matter and flexibility where you need it.

Switching later

Moving between families is a rewrite of the data access layer plus a data migration, not a weekend job. Keep database access behind a thin layer, avoid leaking vendor-specific features everywhere, and keep your schema documented. That lowers the cost, but never to zero.

Common pitfalls

• Choosing NoSQL "to avoid migrations" and then implementing schema checks in application code anyway.
• Choosing a database for scale you do not have. A single well-indexed relational instance carries a long way.
• Skipping indexes and then blaming the database.

Decide on the data and the queries you expect in the first year, not on the trend.