Observability and Automatic Optimization for ORMs.
Qorme is a production-grade SDK that doesn't just monitor your database performance—it actively optimizes it. By combining deep framework instrumentation with real-time ML predictions, Qorme detects and automatically resolves common ORM bottlenecks like N+1 queries and redundant column fetching.
Unlike traditional APM tools that only alert you to problems, Qorme can be configured to automatically optimize your application logic at runtime:
- 🔄 Automatic Prefetching: Resolves N+1 query patterns by dynamically adjusting
prefetch_relatedlookups based on actual usage predictions. - 📉 Intelligent Deferring: Automatically applies
defer()to database columns that your code fetches but never accesses, drastically reducing data transfer and memory usage.
Qorme is designed to scale across multiple frameworks, starting with a deep, native integration for Django:
- Django Integration: Full-spectrum observability and auto-optimization for Django QuerySets and Templates.
- [Future] Core Integrations: Roadmap support for SQLAlchemy, Peewee, and Tortoise ORM.
We organize observability into modular Domains. You can enable or disable these modules to fit your precision requirements:
- Database Drivers: Low-level tracking for SQLite and Psycopg (v2 & v3).
- Background Workers: Automated monitoring for Celery tasks.
- CMS Optimization: Specialized rendering profiling for Wagtail.
- Relational Integrity: Tag-access optimization for Taggit.
- Core Architecture: How the ML Store and Ingest Pipeline work.
- Optimization Guide: Deep dive into ML-driven automatic fixes.
- Configuration Reference: Every knob and tuning parameter.
Apache 2.0. See LICENSE for details.