| 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
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ STACK SELECTION INPUTS โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ โ
โ Project Requirements Team Factors Business Constraintsโ
โ โโโโโโโโโโโโโโโโโโโโ โโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโ โ
โ โข Scale expectations โข Current skills โข Time to market โ
โ โข Performance needs โข Learning capacity โข Budget โ
โ โข Integration points โข Team size โข Hiring market โ
โ โข Compliance/Security โข Experience level โข Long-term support โ
โ โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ
โผ
โโโโโโโโโโโโโโโโโโโ
โ RECOMMENDATION โ
โ Framework โ
โโโโโโโโโโโโโโโโโโโ
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 โโโโโโโโโโ โโโโโโโโโโ โโโโโโโโโโ
Vue โโโโโโโโโโ โโโโโโโโโ โโโโโโโโโโ
Angular โโโโโโโโโโ โโโโโโโโโโ โโโโโโโโโโ
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)
โ
Real-time applications (WebSocket)
โ
I/O-heavy workloads
โ
Full-stack JavaScript teams
โ
Microservices
โ CPU-intensive tasks
โ Heavy computation
## Python (FastAPI/Django)
โ
ML/Data Science integration
โ
Rapid prototyping
โ
Data processing pipelines
โ
Scientific computing
โ High-concurrency I/O
โ Real-time systems
## Go
โ
High-performance services
โ
System programming
โ
Concurrent workloads
โ
Microservices at scale
โ Rapid prototyping
โ Complex ORM needs
## Java (Spring Boot)
โ
Enterprise applications
โ
Complex business logic
โ
Transaction-heavy systems
โ
Large teams
โ Quick MVPs
โ 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?
โโโ YES โ PostgreSQL
โ
โโโ NO โ What's your primary use case?
โโโ General purpose โ PostgreSQL (still!)
โโโ Document storage โ MongoDB
โโโ Caching โ Redis
โโโ Search โ Elasticsearch
โโโ Analytics โ ClickHouse/BigQuery
โโโ Time-series โ TimescaleDB/InfluxDB
โโโ Key-value at scale โ 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
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ MODERN SAAS STACK โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ โ
โ FRONTEND BACKEND DATABASE โ
โ โโโโโโโโโ โโโโโโโ โโโโโโโโ โ
โ Next.js 14 Node.js/Express PostgreSQL โ
โ TypeScript TypeScript Prisma ORM โ
โ Tailwind CSS REST/GraphQL Redis (cache) โ
โ โ
โ INFRASTRUCTURE AUTH PAYMENTS โ
โ โโโโโโโโโโโโโโ โโโโ โโโโโโโโ โ
โ Vercel Clerk/Auth0 Stripe โ
โ AWS S3 NextAuth Stripe Billing โ
โ Cloudflare CDN โ
โ โ
โ MONITORING CI/CD ANALYTICS โ
โ โโโโโโโโโโ โโโโโ โโโโโโโโโ โ
โ Sentry GitHub Actions PostHog/Amplitude โ
โ Datadog Vercel Preview Mixpanel โ
โ โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
Best for: B2B SaaS, 0-1M users
Team size: 2-10 engineers
Time to MVP: 4-8 weeks
Template 2: E-Commerce Platform
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ E-COMMERCE STACK โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ โ
โ FRONTEND BACKEND DATABASE โ
โ โโโโโโโโโ โโโโโโโ โโโโโโโโ โ
โ Next.js (SSR) Node.js/Python PostgreSQL โ
โ TypeScript GraphQL/REST Redis โ
โ Tailwind/Styled Medusa/Custom Elasticsearch โ
โ โ
โ PAYMENTS SHIPPING INVENTORY โ
โ โโโโโโโโ โโโโโโโโ โโโโโโโโโ โ
โ Stripe ShipStation Custom/ERP โ
โ PayPal EasyPost Webhook sync โ
โ โ
โ CDN SEARCH QUEUE โ
โ โโโ โโโโโโ โโโโโ โ
โ CloudFront Algolia/Elastic SQS/BullMQ โ
โ Cloudflare Typesense Redis โ
โ โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
Best for: D2C, Marketplace
Team size: 5-20 engineers
Time to MVP: 8-16 weeks
Template 3: ML-Powered Product
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ ML PRODUCT STACK โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ โ
โ FRONTEND API ML SERVING โ
โ โโโโโโโโโ โโโ โโโโโโโโโโ โ
โ React/Next.js FastAPI TorchServe/Triton โ
โ TypeScript Python Docker/K8s โ
โ Pydantic ONNX Runtime โ
โ โ
โ DATABASE VECTOR DB FEATURE STORE โ
โ โโโโโโโโ โโโโโโโโโ โโโโโโโโโโโโโ โ
โ PostgreSQL Pinecone Feast โ
โ Redis Weaviate Redis โ
โ pgvector โ
โ โ
โ ML OPS TRAINING MONITORING โ
โ โโโโโ โโโโโโโโ โโโโโโโโโโ โ
โ MLflow SageMaker Weights & Biases โ
โ Airflow Vertex AI Prometheus/Grafana โ
โ โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
Best for: AI products, recommendation systems
Team size: 5-15 engineers + ML team
Time to MVP: 12-24 weeks
Template 4: Real-Time Application
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ REAL-TIME STACK โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ โ
โ FRONTEND BACKEND REAL-TIME โ
โ โโโโโโโโโ โโโโโโโ โโโโโโโโโ โ
โ React Node.js Socket.io โ
โ TypeScript Express/Fastify WebSocket โ
โ TypeScript Redis Pub/Sub โ
โ โ
โ DATABASE CACHE MESSAGE QUEUE โ
โ โโโโโโโโ โโโโโ โโโโโโโโโโโโโ โ
โ PostgreSQL Redis Redis Streams โ
โ Prisma In-memory Kafka (scale) โ
โ โ
โ PRESENCE STATE SYNC CONFLICT RESOLUTION โ
โ โโโโโโโโ โโโโโโโโโโ โโโโโโโโโโโโโโโโโโโ โ
โ Redis CRDT/OT Yjs/Automerge โ
โ Custom LiveBlocks Custom โ
โ โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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
โ "Let's use microservices from day one"
โ Start monolith, extract later
โ "We need Kubernetes for our 3-person startup"
โ Use managed platforms (Vercel, Railway)
โ "MongoDB because NoSQL is modern"
โ PostgreSQL handles 95% of use cases better
โ "GraphQL for everything"
โ REST is simpler for most APIs
โ "Let's build our own auth"
โ 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
