dotnet-data-access-strategy

A data access strategy for .NET apps compares EF Core, Dapper, and ADO.NET using a decision matrix to evaluate performance, features, and migration paths. It helps teams select the optimal approach based on specific project constraints and scale.

Choosing between EF Core and Dapper for performance-sensitive .NET components requires evaluating tradeoffs in startup time, memory usage, and query execution speed. The decision matrix highlights when Dapper's lightweight mapping is preferable over EF Core's broader feature set.

A hybrid data access approach mixing EF Core and raw ADO.NET is supported within standard .NET project lifecycles. It allows teams to use EF Core for standard CRUD operations while applying raw ADO.NET or Dapper specifically to performance-critical components.

Migrating from EF Core to Dapper for better data access performance involves following specific migration guidance that weighs learning curves and practical tradeoffs. The strategy outlines paths to transition components while maintaining application stability across typical project lifecycles.

EF Core AOT compilation and trimming considerations are factored into the data access decision matrix. The strategy evaluates whether EF Core's reflection-based features fit AOT requirements, contrasting them against Dapper and raw ADO.NET for trimming compatibility.

You should not use EF Core for .NET data access when memory usage and startup time are critical constraints, or when raw query performance is paramount. The decision matrix identifies these limitations, recommending Dapper or raw ADO.NET for specialized, performance-focused scenarios.