Django's ORM makes database interactions seamless, allowing developers to write queries in Python without raw SQL. However, as applications scale, inefficient queries can slow down performance, leading to high latency and database load. This guide explores advanced query optimization techniques in Django ORM to go beyond basic CRUD (Create, Read, Update, Delete) operations and improve efficiency. 1. Use QuerySet Caching to Avoid Repeated Queries Using cache reduces redundant queries for frequently accessed data. Caching helps reduce repeated database hits. 2. Avoid .count() on Large Datasets Using .count() on large tables can be expensive Inefficient way: Optimized way ( .exists() is Faster) 3. Use Indexes for Faster Lookups Indexes speed up queries on frequently filtered fields. Add db_index=True for frequently queried fields: 4. Optimize Bulk Inserts and Updated Performing operations on multiple records one by one is inefficient. Use bulk_create() for mass insert...