257 lines
7.5 KiB
Markdown
257 lines
7.5 KiB
Markdown
# Backend Technologies
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Core technologies, frameworks, databases, and message queues for modern backend development (2025).
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## Programming Languages
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### Node.js/TypeScript
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**Market Position:** TypeScript dominance in Node.js backend (industry standard)
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**Best For:**
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- Full-stack JavaScript teams
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- Real-time applications (WebSockets, Socket.io)
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- Rapid prototyping with npm ecosystem (2M+ packages)
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- Event-driven architectures
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**Popular Frameworks:**
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- **NestJS** - Enterprise-grade, TypeScript-first, modular architecture
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- **Express** - Lightweight, flexible, most popular (23M weekly downloads)
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- **Fastify** - High performance (20k req/sec vs Express 15k req/sec)
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- **tRPC** - End-to-end typesafe APIs without GraphQL
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**When to Choose:** Team already using JavaScript/TypeScript, real-time features needed, rapid development priority
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### Python
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**Market Position:** FastAPI adoption surge - 73% migrating from Flask
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**Best For:**
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- Data-heavy applications
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- ML/AI integration (TensorFlow, PyTorch)
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- Scientific computing
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- Scripting and automation
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**Popular Frameworks:**
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- **FastAPI** - Modern, async, auto-generated OpenAPI docs, validation via Pydantic
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- **Django** - Batteries-included, ORM, admin panel, authentication
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- **Flask** - Lightweight, flexible, microservices-friendly
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**When to Choose:** Data science integration, ML/AI features, rapid prototyping, team Python expertise
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### Go
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**Market Position:** Preferred for microservices at scale (Docker, Kubernetes written in Go)
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**Best For:**
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- High-concurrency systems (goroutines)
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- Microservices architectures
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- CLI tools and DevOps tooling
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- System programming
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**Popular Frameworks:**
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- **Gin** - Fast HTTP router (40x faster than Martini)
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- **Echo** - High performance, extensible
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- **Fiber** - Express-like API, built on Fasthttp
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**When to Choose:** Microservices, high concurrency needs, DevOps tooling, simple deployment (single binary)
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### Rust
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**Market Position:** 72% most admired language, 1.5x faster than Go
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**Best For:**
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- Performance-critical systems
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- Memory-safe system programming
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- High-reliability requirements
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- WebAssembly backends
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**Popular Frameworks:**
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- **Axum** - Ergonomic, modular, tokio-based
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- **Actix-web** - Fastest web framework (benchmark leader)
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- **Rocket** - Type-safe, easy to use
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**When to Choose:** Maximum performance needed, memory safety critical, low-level control required
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## Databases
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### Relational (SQL)
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#### PostgreSQL
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**Market Position:** Most popular SQL database for new projects
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**Strengths:**
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- ACID compliance, data integrity
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- JSON/JSONB support (hybrid SQL + NoSQL)
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- Full-text search, geospatial (PostGIS)
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- Advanced indexing (B-tree, Hash, GiST, GIN)
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- Window functions, CTEs, materialized views
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**Use Cases:**
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- E-commerce (transactions critical)
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- Financial applications
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- Complex reporting requirements
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- Multi-tenant applications
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**When to Choose:** Need ACID guarantees, complex queries/joins, data integrity critical
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### NoSQL
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#### MongoDB
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**Market Position:** Leading document database
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**Strengths:**
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- Flexible/evolving schemas
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- Horizontal scaling (sharding built-in)
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- Aggregation pipeline (powerful data processing)
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- GridFS for large files
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**Use Cases:**
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- Content management systems
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- Real-time analytics
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- IoT data collection
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- Catalogs with varied attributes
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**When to Choose:** Schema flexibility needed, rapid iteration, horizontal scaling required
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### Caching & In-Memory
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#### Redis
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**Market Position:** Industry standard for caching and session storage
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**Capabilities:**
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- In-memory key-value store
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- Pub/sub messaging
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- Sorted sets (leaderboards)
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- Geospatial indexes
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- Streams (event sourcing)
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**Performance:** 10-100x faster than disk-based databases
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**Use Cases:**
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- Session storage
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- Rate limiting
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- Real-time leaderboards
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- Job queues (Bull, BullMQ)
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- Caching layer (90% DB load reduction)
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**When to Choose:** Need sub-millisecond latency, caching layer, session management
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## ORMs & Database Tools
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### Modern ORMs (2025)
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**Drizzle ORM** (TypeScript)
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- Winning NestJS performance race
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- 7.4kb, zero dependencies
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- SQL-like syntax, full type safety
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- Best for: Performance-critical TypeScript apps
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**Prisma** (TypeScript)
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- Auto-generated type-safe client
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- Database migrations included
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- Excellent DX with Prisma Studio
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- Best for: Rapid development, type safety
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**TypeORM** (TypeScript)
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- Mature, feature-complete
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- Supports Active Record + Data Mapper
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- Best for: Complex enterprise apps
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**SQLAlchemy** (Python)
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- Industry standard Python ORM
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- Powerful query builder
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- Best for: Python backends
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## Message Queues & Event Streaming
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### RabbitMQ
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**Best For:** Task queues, request/reply patterns
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**Strengths:**
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- Flexible routing (direct, topic, fanout, headers)
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- Message acknowledgment and durability
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- Dead letter exchanges
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- Wide protocol support (AMQP, MQTT, STOMP)
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**Use Cases:**
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- Background job processing
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- Microservices communication
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- Email/notification queues
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**When to Choose:** Traditional message queue needs, complex routing, moderate throughput
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### Apache Kafka
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**Best For:** Event streaming, millions messages/second
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**Strengths:**
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- Distributed, fault-tolerant
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- High throughput (millions msg/sec)
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- Message replay (retention-based)
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- Stream processing (Kafka Streams)
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**Use Cases:**
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- Real-time analytics
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- Event sourcing
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- Log aggregation
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- Netflix/Uber scale (billions events/day)
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**When to Choose:** Event streaming, high throughput, event replay needed, real-time analytics
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## Framework Comparisons
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### Node.js Frameworks
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| Framework | Performance | Learning Curve | Use Case |
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|-----------|------------|----------------|----------|
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| Express | Moderate | Easy | Simple APIs, learning |
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| NestJS | Moderate | Steep | Enterprise apps |
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| Fastify | High | Moderate | Performance-critical |
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| tRPC | High | Moderate | Full-stack TypeScript |
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### Python Frameworks
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| Framework | Performance | Features | Use Case |
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|-----------|------------|----------|----------|
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| FastAPI | High | Modern, async | New projects, APIs |
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| Django | Moderate | Batteries-included | Full-featured apps |
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| Flask | Moderate | Minimal | Microservices, simple APIs |
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## Technology Selection Flowchart
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```
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Start → Need real-time features?
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→ Yes → Node.js + Socket.io
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→ No → Need ML/AI integration?
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→ Yes → Python + FastAPI
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→ No → Need maximum performance?
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→ Yes → Rust + Axum
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→ No → Need high concurrency?
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→ Yes → Go + Gin
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→ No → Node.js + NestJS (safe default)
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Database Selection:
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ACID needed? → Yes → PostgreSQL
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→ No → Flexible schema? → Yes → MongoDB
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→ No → PostgreSQL (default)
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Caching needed? → Always use Redis
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Message Queue:
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Millions msg/sec? → Yes → Kafka
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→ No → RabbitMQ
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```
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## Common Pitfalls
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1. **Choosing NoSQL for relational data** - Use PostgreSQL if data has clear relationships
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2. **Not using connection pooling** - Implement pooling for 5-10x performance boost
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3. **Ignoring indexes** - Add indexes to frequently queried columns (30% I/O reduction)
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4. **Over-engineering with microservices** - Start monolith, split when needed
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5. **Not caching** - Redis caching provides 90% DB load reduction
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## Resources
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- **NestJS:** https://nestjs.com
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- **FastAPI:** https://fastapi.tiangolo.com
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- **PostgreSQL:** https://www.postgresql.org/docs/
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- **MongoDB:** https://www.mongodb.com/docs/
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- **Redis:** https://redis.io/docs/
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- **Kafka:** https://kafka.apache.org/documentation/
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