Best Tech Stack for Resume Builder in 2025
Framework comparison, database analysis, and tool recommendations for building a modern resume builder SaaS.
TL;DR: Recommended Stack
Frontend
Next.js 15 + React 19 + TypeScript
Styling
Tailwind CSS + Shadcn/ui
Database
PostgreSQL + Prisma ORM
PDF Generation
Puppeteer (server-side)
Authentication
Clerk or NextAuth.js
Payments
Stripe
Tech Stack Overview
Building a production-ready resume builder requires careful technology selection. The right stack balances developer experience, performance, scalability, and maintainability. This guide compares options based on real-world resume builder requirements.
Key Requirements for Resume Builders
User-Facing Needs
- Fast, responsive editor interface
- Real-time preview updates
- Multiple template rendering
- PDF/DOCX export
- Mobile-friendly design
Technical Needs
- SEO-friendly architecture
- Scalable PDF generation
- Secure authentication
- Payment processing
- Data persistence and backups
Frontend Framework Comparison
| Framework | Pros | Cons | Best For |
|---|---|---|---|
| Next.js 15 | SSR, API routes, SEO, React 19 | Learning curve, Vercel-optimized | Recommended |
| React + Vite | Fast dev, flexible, lightweight | No SSR, separate backend needed | SPAs, existing backend |
| Vue + Nuxt | Great DX, SSR, growing ecosystem | Smaller talent pool | Vue teams |
| Remix | Nested routes, progressive enhancement | Newer, smaller community | Complex routing needs |
Why Next.js 15 Wins
Next.js 15 is the optimal choice for resume builders because:
- Server Components: Faster initial load, better SEO for template gallery pages
- API Routes: Build backend logic alongside frontend, no separate server needed
- Image Optimization: Automatic optimization for template thumbnails
- React 19 Support: Latest React features including improved Suspense
- Edge Functions: Fast PDF generation at the edge
# Create a new Next.js 15 project
npx create-next-app@latest resume-builder --typescript --tailwind --eslint --app
Backend Options
Option 1: Next.js API Routes (Recommended)
For most resume builders, Next.js API routes provide sufficient backend functionality without managing separate infrastructure:
// app/api/resume/route.ts
import { NextResponse } from 'next/server'
import { prisma } from '@/lib/prisma'
import { auth } from '@/lib/auth'
export async function POST(request: Request) {
const session = await auth()
if (!session) {
return NextResponse.json({ error: 'Unauthorized' }, { status: 401 })
}
const data = await request.json()
const resume = await prisma.resume.create({
data: {
userId: session.user.id,
title: data.title,
content: data.content,
templateId: data.templateId,
}
})
return NextResponse.json(resume)
}
Option 2: Separate Backend (Express/Fastify)
Consider a separate backend if you need:
- Microservices architecture
- Heavy background processing
- WebSocket connections for real-time collaboration
- Shared API across multiple frontends
Option 3: Serverless (AWS Lambda, Vercel Functions)
Serverless works well for PDF generation workloads that have variable demand:
- Auto-scaling based on traffic
- Pay-per-execution pricing
- No server management
- Cold start latency trade-off
Database Comparison
| Database | Resume Data | Users/Auth | Payments | Verdict |
|---|---|---|---|---|
| PostgreSQL | Excellent (JSONB) | Excellent | Excellent | Best Choice |
| MongoDB | Excellent | Good | Needs care | Good for flexibility |
| MySQL | Good (JSON) | Excellent | Excellent | Solid alternative |
| Supabase | Excellent | Built-in auth | Excellent | Great DX option |
PostgreSQL + Prisma: The Winning Combination
Prisma provides type-safe database access with excellent developer experience:
// prisma/schema.prisma
model User {
id String @id @default(cuid())
email String @unique
name String?
resumes Resume[]
subscription Subscription?
createdAt DateTime @default(now())
updatedAt DateTime @updatedAt
}
model Resume {
id String @id @default(cuid())
userId String
user User @relation(fields: [userId], references: [id])
title String
templateId String
content Json // Flexible resume data as JSON
isPublic Boolean @default(false)
createdAt DateTime @default(now())
updatedAt DateTime @updatedAt
@@index([userId])
}
model Template {
id String @id @default(cuid())
name String
slug String @unique
thumbnail String
category String // professional, creative, simple, modern
isPremium Boolean @default(false)
config Json // Template-specific configuration
}
PDF Generation Deep Dive
PDF generation is the most technically challenging aspect of resume builders. Here is a comparison of approaches:
| Library | Approach | Quality | Performance | Complexity |
|---|---|---|---|---|
| Puppeteer | HTML → PDF | Pixel-perfect | Moderate | Medium |
| Playwright | HTML → PDF | Pixel-perfect | Good | Medium |
| react-pdf | Programmatic | Good | Fast | High |
| pdfmake | JSON → PDF | Good | Fast | Medium |
| Gotenberg | Docker service | Pixel-perfect | Scalable | High (infra) |
Production-Ready Puppeteer Setup
// lib/pdf-generator.ts
import puppeteer, { Browser } from 'puppeteer'
let browserInstance: Browser | null = null
async function getBrowser(): Promise<Browser> {
if (!browserInstance) {
browserInstance = await puppeteer.launch({
headless: 'new',
args: [
'--no-sandbox',
'--disable-setuid-sandbox',
'--disable-dev-shm-usage',
'--disable-gpu'
]
})
}
return browserInstance
}
export async function generatePDF(html: string): Promise<Buffer> {
const browser = await getBrowser()
const page = await browser.newPage()
try {
await page.setContent(html, {
waitUntil: 'networkidle0',
timeout: 30000
})
// Wait for fonts to load
await page.evaluateHandle('document.fonts.ready')
const pdf = await page.pdf({
format: 'A4',
printBackground: true,
margin: {
top: '0.4in',
right: '0.4in',
bottom: '0.4in',
left: '0.4in'
}
})
return Buffer.from(pdf)
} finally {
await page.close()
}
}
// Cleanup on process exit
process.on('SIGINT', async () => {
if (browserInstance) {
await browserInstance.close()
}
})
Authentication Solutions
Clerk (Recommended)
- Pre-built UI components
- OAuth providers included
- Webhook integrations
- $25/month for 5K MAU
NextAuth.js (Free)
- Open source, free
- 50+ OAuth providers
- Database adapters
- Full control, more setup
Payment Integration
Stripe is the standard choice for SaaS payments. Key features needed:
- Checkout Sessions: Hosted payment page (fastest implementation)
- Customer Portal: Self-service subscription management
- Webhooks: Handle subscription events (created, canceled, updated)
- Price Tables: Embeddable pricing components
// app/api/checkout/route.ts
import { NextResponse } from 'next/server'
import Stripe from 'stripe'
const stripe = new Stripe(process.env.STRIPE_SECRET_KEY!)
export async function POST(request: Request) {
const { priceId, userId } = await request.json()
const session = await stripe.checkout.sessions.create({
mode: 'subscription',
payment_method_types: ['card'],
line_items: [{ price: priceId, quantity: 1 }],
success_url: `${process.env.NEXT_PUBLIC_URL}/dashboard?success=true`,
cancel_url: `${process.env.NEXT_PUBLIC_URL}/pricing?canceled=true`,
metadata: { userId }
})
return NextResponse.json({ url: session.url })
}
AI Integration Options
| Provider | Best For | Cost |
|---|---|---|
| Google Gemini | Resume parsing (vision), content generation | $0.075/1M tokens |
| OpenAI GPT-4 | High-quality text generation | $30/1M input tokens |
| Claude | Long-form content, analysis | $15/1M input tokens |
| Local LLMs | Cost-sensitive, privacy-focused | Hardware only |
For resume parsing with document upload, Google Gemini Vision API offers the best balance of capability and cost. See our AI models comparison for detailed benchmarks.
Deployment & Hosting
| Platform | Best For | Starting Cost |
|---|---|---|
| Vercel | Next.js, zero-config deployment | Free tier, $20/mo Pro |
| Railway | Full-stack with database | $5/mo + usage |
| Render | Containers, background workers | $7/mo per service |
| AWS | Enterprise, full control | Variable, ~$50/mo start |
The Complete Recommended Stack
Production-Ready Resume Builder Stack
Core Framework
- Next.js 15 (App Router)
- React 19
- TypeScript 5.x
- Tailwind CSS 3.x
- Shadcn/ui components
Backend & Data
- PostgreSQL (Neon/Supabase)
- Prisma ORM
- Redis (Upstash) for caching
- S3/R2 for file storage
Features
- Puppeteer for PDF
- Clerk for auth
- Stripe for payments
- Gemini for AI
Infrastructure
- Vercel for hosting
- Sentry for errors
- PostHog for analytics
- Resend for emails
Get This Stack Pre-Built
Skip months of setup with production-ready source code. Includes Next.js 15, React 19, 60+ templates, AI parser, PDF generation, authentication, and Stripe integration. Deploy to Vercel in 15 minutes.
Frequently Asked Questions
Is Next.js or React better for a resume builder?
Next.js is recommended for resume builders because it provides server-side rendering (important for SEO), API routes (backend functionality), and optimized performance out of the box. Plain React requires additional setup for these features.
What database should I use for a resume builder?
PostgreSQL is the best choice for resume builders. It handles structured data well (user accounts, subscriptions) while also supporting JSON columns for flexible resume data. MongoDB works but offers less data integrity for transactional features.
How do I generate PDFs in a resume builder?
The two main approaches are: 1) Puppeteer/Playwright for HTML-to-PDF conversion (pixel-perfect but resource-intensive), or 2) Libraries like react-pdf for programmatic generation (lighter but less flexible). For production, Puppeteer with browser pooling is recommended.
Should I use TypeScript for a resume builder?
Yes, absolutely. TypeScript catches type errors during development, provides better IDE support, and makes refactoring safer. Resume data structures are complex, and TypeScript helps ensure consistency across your codebase.
What hosting is best for a resume builder SaaS?
Vercel is ideal for Next.js resume builders due to zero-configuration deployment, edge functions, and automatic scaling. For more control, AWS/GCP with containerized deployments work well. Expect $50-200/month for moderate traffic.
Written by Pattanaik Ramswarup
AI Engineer & Dataset Architect | Creator of the 77,000 Training Dataset
I've personally trained over 50 AI models from scratch and spent 2,000+ hours optimizing local AI deployments. My 77K dataset project revolutionized how businesses approach AI training. Every guide on this site is based on real hands-on experience, not theory. I test everything on my own hardware before writing about it.
Was this helpful?
Related Guides
Continue your local AI journey with these comprehensive guides