Vercel vs AWS for Startups: Which to Choose?

Vercel vs AWS for Startups

Vercel vs AWS for startups is a question with a surprisingly clear answer for most early-stage teams — but the right answer depends entirely on what you're building and where you are on the growth curve.

Both are legitimate production deployment platforms. But they make opposite tradeoffs: Vercel optimises for developer experience and deployment velocity; AWS optimises for power, flexibility, and scale. Getting the choice wrong in either direction is costly — either you're over-engineered before you've found product-market fit, or you hit a ceiling the week after you do.

Here's how to think through it.

What Vercel Actually Is

Vercel is a deployment platform optimised for front-end frameworks — primarily Next.js (which Vercel created and maintains). You connect a GitHub repo, push code, and Vercel handles builds, CDN distribution, serverless functions, edge middleware, and preview deployments automatically.

For most web applications in 2026, Vercel abstracts away nearly all infrastructure concerns. There's no load balancer to configure, no EC2 instance to patch, no S3 bucket policy to get wrong at 2am. You ship code; Vercel runs it.

What AWS Actually Is

AWS is a cloud infrastructure platform with 200+ services. For most startups, the relevant ones are:

EC2 — virtual machines
ECS/EKS — container orchestration
Lambda — serverless functions
RDS/Aurora — managed relational databases
S3 — object storage
CloudFront — CDN
Amplify — AWS's Vercel-like deployment experience for front-ends

AWS doesn't make decisions for you. It gives you the building blocks and expects you to assemble them correctly. That power comes with real complexity.

Developer Experience: Vercel Wins Decisively

No honest comparison ignores this. Vercel's developer experience is materially better for web application development:

Zero-config deployments — push to main, it's live in ~90 seconds
Preview deployments — every PR gets its own URL automatically
Edge functions — deploy globally with sub-100ms cold starts
Built-in observability — logs, analytics, and web vitals in one dashboard
Environment variables — managed through a clean UI, not IAM policies

Setting up an equivalent AWS deployment with CloudFront + Lambda@Edge + CI/CD + preview environments takes days and requires meaningful devops expertise. For a two-person startup where the founders are also the engineers, that's not time you have.

Cost Comparison

This is where the comparison gets nuanced.

Vercel pricing (2026):

Hobby: Free (personal projects, non-commercial)
Pro: $20/month per seat + usage
Enterprise: Custom

At scale, Vercel can get expensive. Serverless function execution time, bandwidth, and build minutes all have limits. A high-traffic application that could run on a $50/month EC2 instance might cost $300+/month on Vercel at scale.

AWS pricing:

Complex, consumption-based, region-dependent
A minimal production setup (EC2 t3.medium + RDS t3.micro + ALB) runs ~$80–120/month
With Reserved Instances, large workloads are significantly cheaper than equivalent Vercel costs

The crossover point varies by application, but for most startups: Vercel is cheaper per hour of engineering time at early stages; AWS is cheaper per dollar at scale.

AWS Activate (startup credits program) can offset AWS costs significantly — $5,000–$100,000 in credits depending on tier. If you're going AWS, apply on day one.

Scaling and Control

Vercel limitations at scale:

Serverless function execution time: max 60 seconds (Pro), 300 seconds (Enterprise)
No persistent WebSocket connections (though this is improving)
CPU-intensive workloads are expensive per compute unit vs. reserved VMs
Limited control over underlying infrastructure

AWS at scale:

Near-unlimited scaling options
Full control over compute type, networking, and data residency
Spot instances, reserved instances, savings plans — significant cost optimisation available
Container-based workloads (ECS, EKS) can run long-running processes that Vercel serverless can't

If you're building AI applications with GPU requirements, batch processing pipelines, or long-running inference jobs, you will eventually need AWS (or GCP/Azure). Vercel's serverless model doesn't fit those compute patterns.

The Hybrid Architecture (Most Common in Practice)

Most startups end up here: Vercel for the front-end and API routes; AWS for everything else.

Vercel handles the Next.js app — fast deploys, preview URLs, global CDN
AWS RDS handles the database — Postgres on managed infrastructure
AWS S3 handles file storage
AWS Lambda or ECS handles background jobs, AI inference queues, and services that don't fit Vercel's execution model

This hybrid is pragmatic. You get Vercel's excellent DX for what changes most often (the application code) and AWS's flexibility for the infrastructure that needs more control.

It's the same kind of thinking that goes into our build vs buy AI MVP framework — use the right tool for each layer, not one platform for everything.

When to Start With Vercel

Pre-PMF startup moving fast
Next.js, Nuxt, or SvelteKit front-end
Team of 1–5 engineers without dedicated devops
Application is primarily web-serving (not heavy compute or batch processing)
You need preview deployments for design/client review workflows

When to Go AWS From Day One

You're building AI infrastructure with GPU workloads
Your product has strict data residency requirements (certain healthcare, fintech, government sectors)
You have devops capacity or are hiring for it early
You're planning to reach a scale where Vercel's serverless costs become a significant budget line

When to Migrate From Vercel to AWS

The trigger is usually one of:

Monthly Vercel bill exceeds what equivalent AWS infrastructure would cost
You hit Vercel's execution time or compute limitations for specific workloads
Compliance requirements mandate infrastructure control that Vercel can't provide

The good news: if you've built on Next.js with Vercel, migrating to AWS Amplify, Render, or a containerised deployment is feasible. You're not locked in the way you would be with a proprietary framework.

The Bottom Line

For most startups in 2026: start on Vercel. Ship faster, hire devops later, migrate when the bill forces you to or when you hit a real technical ceiling. The time you save on infrastructure in the first 12 months is worth more than the cost delta.

For AI-heavy or compute-intensive startups: plan for a hybrid from day one. Vercel for the front-end; AWS for AI inference, batch jobs, and anything requiring persistent compute.

Want help picking the right infrastructure for your AI product? Our AI MVP playbook covers the full stack decisions we make for clients, and you can reach out directly for a 15-minute scope conversation.

Ready to build with AI? Book a scope call — 15 minutes to scope your project and get a fixed-price quote.

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Vercel vs AWS for Startups: Which to Choose?