| name | tech-stack-recommender |
| description | Recommend technology stacks based on project requirements, team expertise, and constraints. Use when selecting frameworks, languages, databases, and infrastructure for new projects. |
Tech Stack Recommender
Provides structured recommendations for technology stack selection based on project requirements, team constraints, and business goals.
When to Use
- Starting a new project and need stack recommendations
- Evaluating technology options for specific use cases
- Comparing frameworks or languages for a project
- Assessing team readiness for a technology choice
- Planning technology migrations
Stack Selection Framework
Decision Inputs
┌───────────────────────────────────────────────────────────────────┐
│ STACK SELECTION INPUTS │
├───────────────────────────────────────────────────────────────────┤
│ │
│ Project Requirements Team Factors Business Constraints│
│ ──────────────────── ──────────── ────────────────── │
│ • Scale expectations • Current skills • Time to market │
│ • Performance needs • Learning capacity • Budget │
│ • Integration points • Team size • Hiring market │
│ • Compliance/Security • Experience level • Long-term support │
│ │
└───────────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────┐
│ RECOMMENDATION │
│ Framework │
└─────────────────┘
Quick Stack Recommendations
By Project Type
| Project Type | Frontend | Backend | Database | Why |
|---|
| SaaS MVP | Next.js | Node.js/Express | PostgreSQL | Fast iteration, full-stack JS |
| E-commerce | Next.js | Node.js or Python | PostgreSQL + Redis | SEO, caching, transactions |
| Mobile App | React Native | Node.js/Python | PostgreSQL | Cross-platform, shared logic |
| Real-time App | React | Node.js + WebSocket | PostgreSQL + Redis | Event-driven, low latency |
| Data Platform | React | Python/FastAPI | PostgreSQL + ClickHouse | Data processing, analytics |
| Enterprise | React | Java/Spring or .NET | PostgreSQL/Oracle | Stability, enterprise support |
| ML Product | React | Python/FastAPI | PostgreSQL + Vector DB | ML ecosystem, inference |
By Team Profile
| Team Profile | Recommended Stack | Avoid |
|---|
| Full-stack JS | Next.js, Node.js, PostgreSQL | Go, Rust (learning curve) |
| Python Background | FastAPI, React, PostgreSQL | Heavy frontend frameworks |
| Enterprise Java | Spring Boot, React, PostgreSQL | Bleeding-edge tech |
| Startup (Speed) | Next.js, Supabase/Firebase | Complex microservices |
| Scale-Up | React, Go/Node, PostgreSQL | Monolithic frameworks |
Technology Comparison Tables
Frontend Frameworks
| Framework | Best For | Learning Curve | Ecosystem | Hiring |
|---|
| React | Complex UIs, SPAs | Medium | Excellent | Easy |
| Next.js | Full-stack, SSR, SEO | Medium | Excellent | Easy |
| Vue.js | Simpler apps, gradual adoption | Easy | Good | Medium |
| Svelte | Performance-critical | Easy | Growing | Hard |
| Angular | Enterprise, large teams | Hard | Good | Medium |
React vs Vue vs Angular
Speed to MVP Long-term Maint Enterprise Ready
React ████████░░ ████████░░ █████████░
Vue █████████░ ███████░░ ██████░░░░
Angular ██████░░░░ █████████░ ██████████
Backend Frameworks
| Framework | Language | Best For | Performance | Ecosystem |
|---|
| Express | Node.js | APIs, real-time | Good | Excellent |
| Fastify | Node.js | High-performance APIs | Excellent | Good |
| FastAPI | Python | ML APIs, async | Excellent | Good |
| Django | Python | Full-featured apps | Good | Excellent |
| Spring Boot | Java | Enterprise | Good | Excellent |
| Go (Gin/Echo) | Go | High performance | Excellent | Good |
| Rails | Ruby | Rapid prototyping | Moderate | Good |
| NestJS | TypeScript | Structured Node apps | Good | Good |
When to Use What
## Node.js (Express/Fastify/NestJS)
✅ Real-time applications (WebSocket)
✅ I/O-heavy workloads
✅ Full-stack JavaScript teams
✅ Microservices
❌ CPU-intensive tasks
❌ Heavy computation
## Python (FastAPI/Django)
✅ ML/Data Science integration
✅ Rapid prototyping
✅ Data processing pipelines
✅ Scientific computing
❌ High-concurrency I/O
❌ Real-time systems
## Go
✅ High-performance services
✅ System programming
✅ Concurrent workloads
✅ Microservices at scale
❌ Rapid prototyping
❌ Complex ORM needs
## Java (Spring Boot)
✅ Enterprise applications
✅ Complex business logic
✅ Transaction-heavy systems
✅ Large teams
❌ Quick MVPs
❌ Small projects
Databases
| Database | Type | Best For | Scale | Complexity |
|---|
| PostgreSQL | Relational | General purpose, ACID | High | Medium |
| MySQL | Relational | Web apps, read-heavy | High | Low |
| MongoDB | Document | Flexible schemas, JSON | High | Low |
| Redis | Key-Value | Caching, sessions | Very High | Low |
| Elasticsearch | Search | Full-text search | High | Medium |
| ClickHouse | Columnar | Analytics, time-series | Very High | Medium |
| DynamoDB | Key-Value | Serverless, AWS | Very High | Medium |
| Cassandra | Wide-column | Write-heavy, distributed | Very High | High |
Database Selection Guide
Need ACID transactions?
├── YES → PostgreSQL
│
└── NO → What's your primary use case?
├── General purpose → PostgreSQL (still!)
├── Document storage → MongoDB
├── Caching → Redis
├── Search → Elasticsearch
├── Analytics → ClickHouse/BigQuery
├── Time-series → TimescaleDB/InfluxDB
└── Key-value at scale → DynamoDB/Cassandra
Infrastructure
| Platform | Best For | Complexity | Cost |
|---|
| Vercel | Next.js, frontend | Very Low | $ - $$ |
| Railway | Simple deployments | Low | $ - $$ |
| Render | General apps | Low | $ - $$ |
| AWS | Everything, scale | High | $ - $$$$ |
| GCP | ML/Data, Kubernetes | High | $ - $$$$ |
| Azure | Enterprise, .NET | High | $ - $$$$ |
| DigitalOcean | Simple, affordable | Low | $ |
| Fly.io | Edge, global | Medium | $ - $$ |
Stack Templates
Template 1: Modern SaaS Startup
┌──────────────────────────────────────────────────────────────────┐
│ MODERN SAAS STACK │
├──────────────────────────────────────────────────────────────────┤
│ │
│ FRONTEND BACKEND DATABASE │
│ ───────── ─────── ──────── │
│ Next.js 14 Node.js/Express PostgreSQL │
│ TypeScript TypeScript Prisma ORM │
│ Tailwind CSS REST/GraphQL Redis (cache) │
│ │
│ INFRASTRUCTURE AUTH PAYMENTS │
│ ────────────── ──── ──────── │
│ Vercel Clerk/Auth0 Stripe │
│ AWS S3 NextAuth Stripe Billing │
│ Cloudflare CDN │
│ │
│ MONITORING CI/CD ANALYTICS │
│ ────────── ───── ───────── │
│ Sentry GitHub Actions PostHog/Amplitude │
│ Datadog Vercel Preview Mixpanel │
│ │
└──────────────────────────────────────────────────────────────────┘
Best for: B2B SaaS, 0-1M users
Team size: 2-10 engineers
Time to MVP: 4-8 weeks
Template 2: E-Commerce Platform
┌──────────────────────────────────────────────────────────────────┐
│ E-COMMERCE STACK │
├──────────────────────────────────────────────────────────────────┤
│ │
│ FRONTEND BACKEND DATABASE │
│ ───────── ─────── ──────── │
│ Next.js (SSR) Node.js/Python PostgreSQL │
│ TypeScript GraphQL/REST Redis │
│ Tailwind/Styled Medusa/Custom Elasticsearch │
│ │
│ PAYMENTS SHIPPING INVENTORY │
│ ──────── ──────── ───────── │
│ Stripe ShipStation Custom/ERP │
│ PayPal EasyPost Webhook sync │
│ │
│ CDN SEARCH QUEUE │
│ ─── ────── ───── │
│ CloudFront Algolia/Elastic SQS/BullMQ │
│ Cloudflare Typesense Redis │
│ │
└──────────────────────────────────────────────────────────────────┘
Best for: D2C, Marketplace
Team size: 5-20 engineers
Time to MVP: 8-16 weeks
Template 3: ML-Powered Product
┌──────────────────────────────────────────────────────────────────┐
│ ML PRODUCT STACK │
├──────────────────────────────────────────────────────────────────┤
│ │
│ FRONTEND API ML SERVING │
│ ───────── ─── ────────── │
│ React/Next.js FastAPI TorchServe/Triton │
│ TypeScript Python Docker/K8s │
│ Pydantic ONNX Runtime │
│ │
│ DATABASE VECTOR DB FEATURE STORE │
│ ──────── ───────── ───────────── │
│ PostgreSQL Pinecone Feast │
│ Redis Weaviate Redis │
│ pgvector │
│ │
│ ML OPS TRAINING MONITORING │
│ ───── ──────── ────────── │
│ MLflow SageMaker Weights & Biases │
│ Airflow Vertex AI Prometheus/Grafana │
│ │
└──────────────────────────────────────────────────────────────────┘
Best for: AI products, recommendation systems
Team size: 5-15 engineers + ML team
Time to MVP: 12-24 weeks
Template 4: Real-Time Application
┌──────────────────────────────────────────────────────────────────┐
│ REAL-TIME STACK │
├──────────────────────────────────────────────────────────────────┤
│ │
│ FRONTEND BACKEND REAL-TIME │
│ ───────── ─────── ───────── │
│ React Node.js Socket.io │
│ TypeScript Express/Fastify WebSocket │
│ TypeScript Redis Pub/Sub │
│ │
│ DATABASE CACHE MESSAGE QUEUE │
│ ──────── ───── ───────────── │
│ PostgreSQL Redis Redis Streams │
│ Prisma In-memory Kafka (scale) │
│ │
│ PRESENCE STATE SYNC CONFLICT RESOLUTION │
│ ──────── ────────── ─────────────────── │
│ Redis CRDT/OT Yjs/Automerge │
│ Custom LiveBlocks Custom │
│ │
└──────────────────────────────────────────────────────────────────┘
Best for: Chat, collaboration, gaming
Team size: 5-15 engineers
Time to MVP: 8-16 weeks
Technology Trade-off Analysis
Language Selection Matrix
| Factor | JavaScript/TS | Python | Go | Java | Rust |
|---|
| Learning Curve | Low | Low | Medium | Medium | High |
| Ecosystem | Excellent | Excellent | Good | Excellent | Growing |
| Performance | Good | Moderate | Excellent | Good | Excellent |
| Hiring Pool | Large | Large | Medium | Large | Small |
| Type Safety | TS: Good | Optional | Excellent | Excellent | Excellent |
| Memory Safety | GC | GC | GC | GC | Compile-time |
Framework Selection Criteria
## Evaluation Checklist
1. **Team Expertise** (Weight: 30%)
- Current skills alignment?
- Learning curve acceptable?
- Training resources available?
2. **Project Requirements** (Weight: 30%)
- Performance requirements met?
- Feature set complete?
- Scalability path clear?
3. **Ecosystem** (Weight: 20%)
- Package availability?
- Community size?
- Third-party integrations?
4. **Long-term Viability** (Weight: 20%)
- Active maintenance?
- Corporate backing?
- Future roadmap?
Anti-Patterns to Avoid
Technology Selection Red Flags
| Anti-Pattern | Why It's Bad | Better Approach |
|---|
| Resume-Driven | Choosing tech for career, not project | Match to requirements |
| Hype-Driven | Picking latest without evaluation | Proven over trendy |
| Comfort-Only | Only familiar tech even when unsuitable | Evaluate objectively |
| Over-Engineering | Complex stack for simple needs | Start simple |
| Under-Engineering | Simple tools for complex needs | Plan for growth |
Common Mistakes
❌ "Let's use microservices from day one"
→ Start monolith, extract later
❌ "We need Kubernetes for our 3-person startup"
→ Use managed platforms (Vercel, Railway)
❌ "MongoDB because NoSQL is modern"
→ PostgreSQL handles 95% of use cases better
❌ "GraphQL for everything"
→ REST is simpler for most APIs
❌ "Let's build our own auth"
→ Use Auth0, Clerk, or established solutions
Migration Considerations
When to Consider Migration
| Trigger | Action |
|---|
| Performance bottlenecks | Profile first, then consider |
| Team expertise mismatch | Train or hire before migrating |
| End of life/support | Plan 6-12 months ahead |
| Scale limitations | Validate limits with benchmarks |
| Security vulnerabilities | Patch if possible, migrate if not |
Migration Risk Assessment
LOW RISK:
- Library/package updates
- Minor version upgrades
- Adding new services
MEDIUM RISK:
- Database version upgrades
- Framework major versions
- New deployment platform
HIGH RISK:
- Language/framework rewrites
- Database technology changes
- Monolith to microservices
Quick Reference
"I'm building a..."
| Project | Recommended Stack |
|---|
| Blog/CMS | Next.js + Headless CMS (Sanity/Contentful) |
| SaaS Dashboard | Next.js + Node.js + PostgreSQL |
| Mobile App | React Native + Node.js + PostgreSQL |
| E-commerce | Next.js + Medusa/Custom + PostgreSQL |
| Real-time Chat | React + Node.js + Socket.io + Redis |
| Data Dashboard | React + Python/FastAPI + PostgreSQL |
| ML Product | React + Python/FastAPI + PostgreSQL + Vector DB |
| API Service | Node.js or Python + PostgreSQL |
Stack Complexity Levels
| Complexity | Description | Example Stack |
|---|
| Minimal | Single deployment, managed services | Vercel + Supabase |
| Simple | Separate frontend/backend | Vercel + Railway + PostgreSQL |
| Standard | Multiple services, caching | AWS ECS + RDS + Redis |
| Complex | Microservices, event-driven | K8s + Multiple DBs + Kafka |
References
