Entity Framework Core introduces the Code-First approach, allowing developers to define the model using code rather than through a visual designer. This offers greater flexibility and advanced capabilities in defining and customizing the database model.

Entity Framework Core handles data loading differently, particularly in how it performs eager loading, lazy loading, and explicit loading. Understanding these differences is crucial for optimizing performance and scalability in applications.

Entity Framework Core provides enhanced support for JSON serialization, enabling seamless integration with modern cloud services that often rely on JSON data. This enhanced support contributes to better performance and interoperability in cloud-based applications.

Entity Framework Core is specifically designed for cross-platform development, offering support for multiple platforms including Windows, Linux, and macOS. It is a lightweight, extensible, and open-source ORM framework that works well with .NET Core and .NET 5+ projects, making it the preferred choice for cross-platform applications.

Entity Framework Core is optimized for high-performance scenarios, including batch processing, due to its lightweight nature and improved performance over previous versions. It offers better memory management, faster query execution, and support for modern database features, making it the preferred choice for projects requiring high-performance batch processing.

Data Annotations in Entity Framework primarily serve for data validation purposes. They allow developers to specify constraints directly on the entity properties, such as maximum length, required fields, and regular expressions for data format. This helps ensure data integrity at the application level before interacting with the database.

Fluent API in Entity Framework allows for defining complex relationships between entities using fluent syntax. This flexibility includes specifying custom naming conventions for foreign keys, mapping entities to different tables, defining cascading delete behavior, and more. Unlike Data Annotations, Fluent API provides a programmatic way to configure relationships, which can be more powerful and expressive, especially in scenarios involving complex data models or when you need to define relationships that cannot be expressed using attributes alone.

Fluent API allows for configuring relationships without modifying the entity classes directly. This approach is particularly useful in scenarios where you cannot or prefer not to modify the entity classes, such as when working with entities generated from a database schema or when you want to keep your entity classes clean and focused solely on representing the domain model. By using Fluent API, you can configure relationships, define constraints, and customize other aspects of the model without cluttering the entity classes with mapping information or attributes.

Data Annotations offer a simpler and more straightforward way to configure entity relationships by directly decorating entity classes with attributes. In a simple Entity Framework model where the relationships are straightforward and don't require complex configurations or custom conventions, Data Annotations can be more convenient and intuitive to use. They reduce the need for additional configuration files or separate fluent API code, making the codebase more concise and easier to understand for developers familiar with attribute-based configuration. However, Data Annotations may lack the flexibility and expressiveness of Fluent API in more complex scenarios.

Data Annotations in Entity Framework provide a convenient way to configure relationships directly within the model classes using attributes. However, they have limitations when it comes to handling complex relationship configurations, such as many-to-many. Data Annotations lack the expressiveness and flexibility offered by Fluent API, making it challenging to define intricate mappings or handle scenarios that deviate from the standard conventions.