database-performance

To avoid N+1 queries and Cartesian explosions in EF Core, you should perform joins in SQL and use `AsSplitQuery` for related data, ensuring efficient database access patterns by fetching necessary data without creating excessive round trips.

The best way to optimize database read queries is by enforcing read/write model separation using CQRS, applying row limits, and using `AsNoTracking` for read-only operations to fetch only necessary data efficiently.

You should use Dapper instead of EF Core for complex read operations where performance is critical. EF Core is suitable for general data manipulation, but Dapper provides better performance for specialized, complex read queries.

Yes, using `AsNoTracking` improves EF Core read performance by bypassing the change tracker. This reduces memory overhead and processing time for read-only queries, making database access patterns more efficient.

Application-side joins are an anti-pattern because they fetch unjoined data across multiple queries and merge it in memory. Performing joins directly in SQL is faster, reduces network traffic, and leverages the database's query optimization engine.

To implement CQRS patterns, you separate your read and write data models completely. This allows you to optimize read queries for specific views using `AsNoTracking` and Dapper, while using EF Core for transactional write operations.