tech-stack-recommender

# 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 ```markdown ## 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 ```markdown ## 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 ```markdown ❌ "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 | |---------|-------------------|