"Which database should we use?" is one of the first questions every SaaS team asks — and one of the easiest to get wrong by following a blog headline instead of your actual workload. Here is how we decide between MongoDB and PostgreSQL for SaaS products.
The short answer
- Choose PostgreSQL when your data is relational, you need transactions across multiple entities, and reporting/analytics matters. This covers the majority of B2B SaaS.
- Choose MongoDB when your data is document-shaped, schemas vary per customer, and you are optimising for flexible, fast iteration on nested data.
Most SaaS products we build start on PostgreSQL. But "it depends" is real — let us break it down.
Data model fit
PostgreSQL is a relational database with rich SQL, foreign keys and strong constraints. If your domain is naturally tabular — users, organisations, subscriptions, invoices, line items — relations keep your data correct.
MongoDB stores JSON-like documents. It shines when an entity is a self-contained tree (a CMS page, an IoT reading, a flexible product catalogue) and when different tenants legitimately need different fields.
Rule of thumb: if you find yourself writing many JOINs, you want PostgreSQL. If you keep flattening everything into one big document, MongoDB may fit better.
Transactions and consistency
For SaaS billing, you cannot afford a half-applied payment. PostgreSQL has had robust ACID transactions for decades. MongoDB added multi-document transactions in 4.0, and they work — but they are a feature you reach for, not the default, and they carry performance caveats at scale.
If money, inventory or anything that must reconcile exactly flows through your app, the relational model is the safer default.
Schema evolution
This is where MongoDB earns its reputation. Adding a field to a document is free; no migration. For early-stage products iterating weekly, that speed is genuinely useful.
PostgreSQL needs migrations — but with tools like Prisma Migrate, Flyway or Liquibase this is a solved problem, and the discipline catches data-shape bugs before they reach production. Modern PostgreSQL also has a first-class JSONB type, so you can store flexible documents inside a relational database and index them. In practice this gives you 80% of MongoDB's flexibility without giving up relations.
Multi-tenancy
For a multi-tenant SaaS you have three common strategies, and both databases support them:
- Shared schema, tenant_id column — simplest, most common, cheapest.
- Schema-per-tenant — stronger isolation (PostgreSQL schemas are great here).
- Database-per-tenant — maximum isolation, highest operational cost.
PostgreSQL's row-level security (RLS) is a standout feature for shared-schema multi-tenancy — you can enforce tenant isolation at the database layer, not just in application code. MongoDB does not have a direct equivalent.
Scaling
MongoDB was designed for horizontal scaling (sharding) from the start, which historically made it attractive for very high write volumes. PostgreSQL scales vertically extremely well, and with read replicas, partitioning and tools like Citus it scales horizontally too. For 99% of SaaS companies, a well-indexed PostgreSQL instance handles more load than they will ever reach before they can afford a DBA.
Cost and operations
Managed options are mature on both sides — MongoDB Atlas, and PostgreSQL on AWS RDS/Aurora, Google Cloud SQL, Supabase or Neon. PostgreSQL's open-source licensing and broad hosting competition tend to make it cheaper to run at small-to-mid scale.
Our default recommendation
For a typical B2B SaaS — accounts, billing, dashboards, reporting — we start with PostgreSQL + JSONB for flexible fields, RLS for tenant isolation and Prisma for type-safe access. We reach for MongoDB when the core domain is genuinely document-centric or schema varies wildly per tenant.
Want a recommendation for your specific product? Book a free architecture call and we will map it to your data and growth plan.