Python-Powered Performance
Built with Python for reliable, maintainable performance. Fast enough for real users, simple enough for one developer to manage.
Fast enough for great user experience
Reliable, ACID-compliant data storage
Handle real-world traffic smoothly
Add servers as you grow
Modern Python
Python 3.11+ with performance improvements
- 25% faster than Python 3.10
- Efficient memory management
- Native async/await support
- Rich standard library
Smart Caching
Simple caching for faster responses
- In-memory caching with Redis
- Function-level caching
- Database query caching
- Session storage optimization
Static Assets
Efficient static file handling
- Gzip compression enabled
- Browser caching headers
- CDN-ready delivery
- Optimized asset bundling
PostgreSQL Power
World-class open source database
- JSONB for flexible data
- Full-text search built-in
- Reliable ACID transactions
- Scales to millions of rows
Async Processing
Handle concurrent operations efficiently
- Async I/O with asyncio
- Background task queues
- Non-blocking requests
- Real-time capabilities
Production Ready
Battle-tested deployment stack
- WSGI/ASGI server support
- Nginx reverse proxy
- Docker containerization
- Easy horizontal scaling
Realistic performance expectations for a Python MVP on modest hardware
Response Times
Scalability
Developer Experience
Profiling Tools
Built-in performance insights during development
- Python's cProfile for bottlenecks
- SQL query logging and analysis
- Memory profiling with tracemalloc
- Response time monitoring
- Free built-in tools
Simple Monitoring
Lightweight tools for production visibility
- Application logging to files
- Error tracking with Sentry (free tier)
- Server metrics via SSH/htop
- PostgreSQL pg_stat_statements
- Uptime monitoring (UptimeRobot)
Query Optimization
Database performance without complexity
- Use connection pooling
- Optimize slow queries with EXPLAIN
- Add indexes to filtered/sorted fields
- Use prepared statements
- Monitor query execution times
Caching Strategy
Simple caching that makes a big difference
- Cache expensive database queries
- Use Redis for session storage
- Implement function-level caching
- HTTP caching headers
- Reasonable cache timeouts
Python Logging
Built-in logging for errors and performance
- Standard library logging module
- Log to files or console
- Custom log levels and handlers
- Error notifications via email
- Free and straightforward
Server Basics
Simple server monitoring you can check
- htop for CPU and memory
- df for disk usage
- PostgreSQL activity queries
- Nginx access logs
- Set up in minutes
Error Tracking
Catch errors before users report them
- Sentry free tier (5k events/mo)
- Stack traces and context
- Email notifications
- Performance monitoring included
- Easy Python integration
Uptime Checks
Know when your site goes down
- UptimeRobot (free for 50 monitors)
- Ping every 5 minutes
- Email/SMS alerts
- Public status page option
- No credit card required
Response Time
< 500msAverage response time for typical requests under normal load
Uptime
99.9%System availability with proper infrastructure setup
Concurrent Users
100+Handle concurrent users smoothly on recommended hardware
Database Performance
Millions of rowsPostgreSQL handles millions of records efficiently
See the Performance Yourself
Try our platform and experience enterprise-grade performance