Prompt

What database should I use for a SaaS app with users and billing?

Technology / Databases1 observationLast seen Oct 7, 2026

Latest observation

Oct 7, 2026OpenAI APIWeb search: off

For most SaaS apps with users and billing, the best default choice is PostgreSQL.

Why PostgreSQL is usually the best fit

  • Great for relational data: users, subscriptions, invoices, payments, organizations, roles, etc.
  • Strong consistency: important for billing and access control.
  • Flexible: handles structured data well and can also store JSON when needed.
  • Mature ecosystem: works well with ORMs, migrations, background jobs, and analytics tools.
  • Easy to scale initially: plenty fast for a startup to mid-size SaaS.

Typical SaaS data model in Postgres

  • users
  • organizations / accounts
  • memberships
  • plans
  • subscriptions
  • invoices
  • payments
  • audit_logs

Common stack choice

  • PostgreSQL as the main database
  • Redis for caching, sessions, rate limiting, and job queues
  • Optional:
    • Object storage (S3, etc.) for files
    • Analytics DB later if reporting gets heavy

When you might choose something else

  • MySQL: also fine, especially if your team already knows it well
  • MongoDB: usually not ideal as the primary DB for billing-heavy SaaS
  • DynamoDB / NoSQL: useful for very specific high-scale access patterns, but usually overkill early on
  • SQLite: good for prototypes, not ideal for multi-user production billing apps

Important billing advice

Billing data should be treated carefully:

  • Use transactions
  • Keep an immutable payments/invoices ledger
  • Don’t rely only on Stripe/webhook state without reconciliation
  • Store provider IDs and event IDs for idempotency

Practical recommendation

If you’re starting a SaaS today:

  1. Use PostgreSQL
  2. Use Stripe for billing
  3. Add Redis if/when you need caching or background jobs

If you want, I can also suggest a full SaaS stack (database, auth, billing, queue, hosting) based on your app size and language/framework.

Observation history

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