Tech Stack Selection Guide

Choosing the right technology stack is one of the most consequential decisions in any web project. This guide walks you through the key considerations and tradeoffs to help you make an informed choice.

The Decision Framework

Before comparing specific technologies, establish your constraints:

Project Requirements

The "Boring Technology" Principle

Dan McKinley's famous essay argues that every company gets roughly three "innovation tokens" to spend. Choose proven technology for most things, and only innovate where it creates a real competitive advantage.

Rule of thumb: If you are unsure, pick the most popular option. It will have better documentation, more Stack Overflow answers, and a larger hiring pool.

Frontend Frameworks

React (Next.js)

Best for: Most web applications, especially those needing SSR/SSG.

React dominates the market with the largest ecosystem. Next.js adds server-side rendering, file-based routing, and API routes out of the box.

Vue (Nuxt)

Best for: Teams that prefer a gentler learning curve and a more opinionated framework.

Vue offers a progressive adoption model. Nuxt provides the same SSR/SSG capabilities as Next.js but with Vue's composition API.

Svelte (SvelteKit)

Best for: Performance-critical applications and developers who dislike virtual DOM overhead.

Svelte compiles components at build time, producing minimal JavaScript. SvelteKit handles routing and SSR.

When to Choose What

Backend Options

Node.js (Express / Fastify / Hono)

The natural choice when your frontend is JavaScript/TypeScript. Sharing types across the stack eliminates a whole class of bugs.

• Express: Battle-tested, massive middleware ecosystem
• Fastify: Better performance, schema-based validation
• Hono: Ultrafast, runs on edge runtimes (Cloudflare Workers, Deno, Bun)

Python (Django / FastAPI)

Python excels at data-heavy applications. Django provides an admin panel, ORM, and authentication out of the box. FastAPI is ideal for building high-performance APIs with automatic OpenAPI documentation.

Go

For services where raw performance and low memory usage matter. Go's standard library is remarkably complete for building HTTP servers. Ideal for microservices and CLI tools.

Rust (Actix / Axum)

Maximum performance at the cost of development speed. Choose Rust when you need predictable latency and minimal resource usage.

Database Selection

Relational (PostgreSQL)

PostgreSQL is the default choice for most applications. It handles JSON, full-text search, geospatial queries, and more.

Document (MongoDB)

Best for applications with highly variable schemas. Be cautious -- many projects that start with MongoDB eventually migrate to PostgreSQL.

Key-Value / Cache (Redis)

Use Redis as a caching layer, session store, or message broker.

Choosing a Database

ORM and Query Builders

Recommendation: Drizzle ORM for TypeScript projects. It stays close to SQL, provides excellent type inference, and generates efficient queries.

Deployment and Infrastructure

Platform-as-a-Service

Backend-as-a-Service

Recommended Stacks

Solo Developer / Startup MVP

Small Team (2-5 developers)

Enterprise / Large Team

Decision Checklist

Before finalizing your stack, verify:

• Does the team have experience with these tools?
• Is hiring realistic for this stack in your market?
• Are there production case studies at your expected scale?
• Is the documentation comprehensive and up-to-date?
• Does the license allow commercial use?
• Is there an active community for troubleshooting?

Final Advice

The best stack is the one your team can ship with. Avoid "resume-driven development" -- picking technologies because they look good on a CV rather than because they solve your problem. Ship early, gather feedback, and refactor later when you understand your real requirements.