How to Choose the Right Technology Stack for a SaaS Product

Stack arguments consume more founder hours than almost any other technical topic, and most of the argument is about choices you could reverse in a fortnight. Four decisions are genuinely expensive to undo. Spend your thinking there.

The four that matter

1. Your database

For SaaS, start with PostgreSQL unless you have a specific reason not to. Subscription billing, permissions, usage limits and reporting are all relational problems, and transactional integrity is not optional when money is involved. Postgres also does JSON well, so the flexibility argument for a document store is weaker than it was.

Choose MongoDB when your core data genuinely varies in shape per record and you do not need multi-record transactions. Choose it because that is true, not because it was faster to start with.

2. Your tenancy model

How one customer's data is separated from another's: a tenant column, a schema per tenant, or a database per tenant. This is the decision people postpone and then pay for, because retrofitting isolation into a live product touches every query you have written.

Row-level with a tenant key is right for most products. Schema or database per tenant is for compliance requirements or enterprise customers who contractually demand it. Decide in week one — the detail is in multi-tenant SaaS architecture.

3. Authentication

Build it, or buy it from Auth0, Clerk or similar. Buying is usually right early: SSO, MFA and password resets are a lot of unglamorous work. Just check the pricing curve at the scale you are planning for, because auth providers are cheap at 1,000 users and surprising at 100,000.

4. Hosting

A managed platform like Vercel or Railway until you have a reason for AWS. The reason usually arrives as compliance, data residency, or a workload that does not fit serverless. Starting on AWS "because we will need it" buys you an operational burden a year before the benefit — see cloud and DevOps.

What matters more than elegance: who will write it

The most underweighted criterion in stack selection is hiring. A stack that three people in your city write is a recruitment problem within a year, and a retention problem the moment one of them leaves. TypeScript across React, Next.js and Node is not the most interesting answer, but one language across the stack means any engineer can work anywhere in the codebase and you can actually hire them — which is why it is our default for SaaS builds.

Where boring wins

• Background jobs. A queue with retries. Not an event-sourced architecture for sending welcome emails.

• Search. Postgres full-text until it genuinely is not enough. Elasticsearch is a system to operate, not a feature to add.

• Caching. Redis. There is no interesting answer here and you do not want one.

• Monolith first. Microservices solve an organisational problem you do not have at six engineers, and they add a distributed-systems problem you definitely do not want.

What is cheap to change later

Relax about these: CSS framework, component library, state management, hosting region, the exact Node framework, your CI provider. Each is a week of work to swap. They attract the most debate precisely because everyone has an opinion and nothing is at stake.

A short checklist before you commit

• Can we hire for this in our market, at our budget?

• Is the tenancy model written down and agreed?

• Does the database fit the shape of the data, or the shape of our habits?

• What does this cost at 10x our current plan's usage?

• If this vendor disappeared, how long to replace them?

Frequently Asked Questions

Should I use a framework like Next.js for a SaaS app?

Yes, usually. You get the marketing site and the application in one codebase, with server rendering where it helps SEO and client rendering where it does not matter. See Next.js vs React.

Is it worth using a new framework to move faster?

Occasionally. Weigh it against the hiring question and whether it will still be maintained in three years. Novelty has a real cost that shows up long after the decision.

How long does a SaaS MVP take?

Two to four weeks for a focused first release with auth, a database and the core flow — see how long it takes to build a SaaS.

Can you just decide this for us?

That is what fractional CTO advisory is for: architecture reviews and written decision records, priced separately so the advice does not have to sell you a build.