Comparing .NET EF Core and Dapper: A Developer's Guide

When it comes to data access in the .NET ecosystem, Entity Framework Core (EF Core) and Dapper are among the most popular choices. Both libraries offer a set of high-level APIs for interacting with relational databases, but they differ significantly in terms of complexity, performance, and flexibility. In this blog post, we'll compare these two libraries to help you make an informed decision for your next .NET project.

Introduction

Entity Framework Core (EF Core)

Entity Framework Core is an Object-Relational Mapping (ORM) framework developed by Microsoft. It allows developers to work with databases using .NET objects, abstracting much of the underlying database interactions. It's a feature-rich, extensible, and highly configurable framework that provides everything from data retrieval to data modeling.

Dapper

Dapper is a micro-ORM, also built for the .NET ecosystem. It was developed by the Stack Overflow team and is more lightweight compared to EF Core. Dapper provides a set of helper functions for executing raw SQL queries, offering a performance-optimized, straightforward approach to data access.

Comparison Criteria

1. Ease of Use
2. Performance
3. Flexibility
4. Community and Support
5. Advanced Features

Ease of Use

EF Core

• Code-First Approach: EF Core allows developers to define database schema using C# classes.
• LINQ Support: Offers seamless integration with LINQ, making data queries more intuitive.
• Database Migrations: Built-in support for database migrations and schema management.

Dapper

• SQL-Centric: Requires writing raw SQL queries, which could be more intuitive for those familiar with SQL.
• Less Boilerplate: Typically requires less boilerplate code for simple CRUD operations.

Performance

EF Core

• Overhead: The abstraction layer and additional features can introduce performance overhead.
• Lazy Loading: Offers lazy loading, which can be both an advantage and a drawback based on use-case.

Dapper

• Speed: Known for high-performance data access, as it's closer to raw SQL.
• No Overhead: Minimal abstraction layer means less overhead.

Flexibility

EF Core

• Extensible: Highly configurable and extensible, allowing for a wide range of customization.
• Multiple Database Support: Built-in support for multiple database providers.

Dapper

• Focused: Does one thing (data access) and does it well.
• Custom Queries: Since you write raw SQL, you have complete control over the queries.

Community and Support

EF Core

• Strong Community: Being a Microsoft product, it has a strong community and extensive documentation.
• Regular Updates: Regularly updated with new features and performance improvements.

Dapper

• Growing Community: Although smaller than EF Core, the community is active and growing.
• Good Documentation: Adequate documentation and plenty of third-party tutorials.

Advanced Features

EF Core

• Change Tracking: Automatically tracks changes to entities and updates them in the database.
• Relationship Management: Built-in support for managing complex relationships, transactions, and joins.

Dapper

• Batch Queries: Supports batch querying and multiple result sets.
• Stored Procedures: Easy to call stored procedures and map results.

Here is the working sample for the Entity Framework Core.

public class Product
{
    public int Id { get; set; }
    public string Name { get; set; }
    public decimal Price { get; set; }
}        

Now, let's define the DbContext

public class AppDbContext : DbContext
{
    public DbSet<Product> Products { get; set; }

    protected override void OnConfiguring(DbContextOptionsBuilder optionsBuilder)
    {
        optionsBuilder.UseSqlServer("YourConnectionStringHere");
    }
}        

CRUD Operations

// Create
using (var context = new AppDbContext())
{
    var product = new Product { Name = "Laptop", Price = 1000M };
    context.Products.Add(product);
    context.SaveChanges();
}

// Read
using (var context = new AppDbContext())
{
    var product = context.Products.Find(1);
    Console.WriteLine(product.Name);
}

// Update
using (var context = new AppDbContext())
{
    var product = context.Products.Find(1);
    product.Price = 1200M;
    context.SaveChanges();
}

// Delete
using (var context = new AppDbContext())
{
    var product = context.Products.Find(1);
    context.Products.Remove(product);
    context.SaveChanges();
}        

Now, let's look at Dapper example:

First, let's define the Product class, similar to the EF Core example.

public class Product
{
    public int Id { get; set; }
    public string Name { get; set; }
    public decimal Price { get; set; }
}        

CRUD Operations

using System.Data.SqlClient;
using Dapper;

// Create
using (var connection = new SqlConnection("YourConnectionStringHere"))
{
    var product = new Product { Name = "Laptop", Price = 1000M };
    connection.Execute("INSERT INTO Products (Name, Price) VALUES (@Name, @Price)", product);
}

// Read
using (var connection = new SqlConnection("YourConnectionStringHere"))
{
    var product = connection.QueryFirstOrDefault<Product>("SELECT * FROM Products WHERE Id = @Id", new { Id = 1 });
    Console.WriteLine(product.Name);
}

// Update
using (var connection = new SqlConnection("YourConnectionStringHere"))
{
    var product = new Product { Id = 1, Price = 1200M };
    connection.Execute("UPDATE Products SET Price = @Price WHERE Id = @Id", product);
}

// Delete
using (var connection = new SqlConnection("YourConnectionStringHere"))
{
    connection.Execute("DELETE FROM Products WHERE Id = @Id", new { Id = 1 });
}        

Conclusion

Choosing between EF Core and Dapper depends on your project's needs. If you need a full-featured ORM with advanced capabilities and don't mind the extra overhead, EF Core is the way to go. On the other hand, if you need a lightweight, high-performance library and are comfortable with SQL, Dapper could be a better fit.

Both libraries have their strengths and weaknesses, and the "best" choice is highly contextual. Consider your team's expertise, your project's requirements, and your performance needs when making a decision.

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