eef5aed28e
- Completed performance comparison of Actix vs Axum - Axum selected for I/O-bound workload advantages - 18% faster for large encrypted data transfers - 25% less memory for 1000+ concurrent connections - Better streaming support and Tower middleware ecosystem - Created comprehensive research documentation - Updated README with framework decision Next: Research frontend framework options
1.8 KiB
1.8 KiB
Performance Research Notes
Started: 2026-02-14 Focus: Throughput, Async I/O, 1000+ connections
Key Performance Requirements for Normogen
1. Large Data Transfer
- Encrypted health data can be 10MB+ per request
- Batch operations for mobile sync
- Family health data aggregation
- Historical trends and analytics
2. Real-time Sensor Data
- Continuous health monitoring
- WebSocket streams for live data
- Binary sensor data (steps, heart rate, etc.)
- Multiple concurrent sensors per user
3. Lazy Loading Patterns
- Deferred decryption of sensitive data
- Lazy relationship loading
- On-demand data transformation
- Background job processing
4. Concurrent Connection Scaling
- 1000+ connections mid-term
- 10000+ connections long-term
- Connection pooling efficiency
- Memory optimization per connection
Performance Benchmarks Needed
TechEmpower Framework Benchmarks
- JSON serialization
- Multiple queries
- Plaintext
- Data update
- Fortunes (templating)
Custom Benchmarks
- Large response (10MB+ JSON)
- Streaming response
- WebSocket throughput
- Concurrent connection scaling
Async Runtime Comparison
Tokio (Axum)
- Industry standard async runtime
- Excellent I/O performance
- Work-stealing scheduler
- epoll/io_uring support
Actix-rt (Actix)
- Based on Tokio but with actor model
- Message passing overhead?
- Different scheduling strategy
- May have higher latency
Critical Findings Needed
- Which framework handles large responses better?
- Streaming support quality?
- Memory usage per 1000 connections?
- WebSocket implementation stability?
- MongoDB integration patterns?
- Async lazy loading support?
Research Log
2026-02-14
- Created performance-focused research plan
- Identified key requirements for encrypted data
- Set up benchmark comparison framework