Building a .NET application that interacts with a database? You’ll need a way to manage data efficiently. While you still can write raw SQL queries manually, that approach might get you in all kinds of trouble, from slower development because of repetitive code and having to troubleshoot performance issues due to clumsy queries to higher project maintenance costs whenever your database has changes in its schema. That’s where ORM (Object-Relational Mapping) comes in, making database interactions faster, safer, and easier to maintain, as it:
- Eliminates repetitive SQL writing. With ORM, instead of writing raw SQL, you work with C# objects and methods to fetch, update, and delete data.
- Ensures security against SQL injection. ORMs use parameterized queries, preventing common injection attacks.
- Handles relationships & transactions. ORMs manage foreign keys, joins, and transactions, reducing the risk of broken queries or inconsistent data.
- Assists in performance optimization. ORMs optimize queries with lazy loading, eager loading, and caching to improve speed. Moreover, some ORMs allow fine-tuning to prevent unnecessary database calls.
- Provides schema flexibility. If you change the database structure, you don’t need to rewrite every query since ORMs can adapt using migrations.
It goes without saying that ORMs can become your perfect allies in building .NET applications, saving you tons of time and effort. However, when you check which options are available on the market, you can easily get dazed by loads of information, some of which can be outdated or irrelevant to your project. For one, if your project requires simple CRUD operations and quick development, Entity Framework Core is the best choice. But then, there are some faster options that reportedly provide better performance, which you can also go for.
In this article, we’ll overview top 9 .NET ORMs, and will try to help you pick the best ORM for .NET Core for your future projects.
Table of contents
- Criteria for selecting the best .NET ORM
- Top 9 .NET ORM solutions
- Comparison
- Best practices for using ORMs in .NET
- Enhancing ORM with Devart tools
- Conclusion
Criteria for selecting the best .NET ORM
Choosing the right .NET ORM isn’t about picking the “best” one — it’s about finding the right fit for your project. Consider your application’s needs, database structure, and performance requirements before making a decision. Here are some criteria you should consider before committing to any of the options.
1. Use case
Your choice should align with your project’s specific requirements. Some ORMs are better suited for high-performance applications, while others prioritize flexibility. Define your priorities before deciding.
2. Expected number of users
The choice of a .NET ORM depends a lot on the scenarios of how your app is going to be used, and especially on the number of users it’s going to have. If it’s just a single-user scenario, most ORMs will work. However, in multi-user apps, one should consider how the ORMs will act when several users modify data at the same time.
3. Locking and caching
Some ORMs cache data to boost performance but risk showing outdated information. Others work directly with the database for real-time accuracy.
4. Application type
Particlular .NET ORMs fit better for web apps since they can handle high request loads and show top performance, while for desktop apps, you can opt for more feature-rich ORM solutions.
5. Support of database features
Most ORMs use generic SQL to stay compatible with multiple databases, but that can mean losing access to database-specific features (full-text search, advanced indexing).
6. Handling of data model updates
Some .NET ORMs automate database migrations, saving time, while others require manual updates, offering more control but adding maintenance overhead. Thus, you should choose an ORM based on your team’s workflow and the project’s complexity.
7. Dependencies in ORM-specific data objects
Some ORMs tie your application logic to ORM-specific objects, making switching databases harder. Others allow POCOs (Plain Old CLR Objects), keeping data models separate from ORM logic, but require more setup.
8. Ability to fetch data from a remote server
If your app fetches data from a remote server, some ORMs handle this more efficiently than others. Look into how well it manages lazy loading, batching, and serialization.
9. Learning curve
Comprehensive documentation and community support can save you when issues arise. Check forums, GitHub issues, and commercial support options before committing.
Picking the right .NET ORM can save you development time, reduce maintenance headaches, and improve performance. Define your project’s needs first, then find the ORM that fits you best — you don’t have to settle for a one-size-fits-all solution.
Top 9 .NET ORM solutions
Let’s explore the top proven ORM solutions for .NET in 2025:
1. Entity Framework Core (EF Core)
EF Core is a modern, cross-platform .NET ORM that simplifies database access in applications. It supports multiple databases, LINQ queries, automatic schema migrations, and change tracking, making it a powerful choice for developers who want to reduce manual SQL writing.
Key features:
- Productivity. Eliminates the need for hard-coded SQL by enabling LINQ-based queries, lowering the learning curve.
- Maintainability & security. Built-in SQL query management reduces the risk of SQL injection.
- Cross-platform support. Runs on .NET Core, making it compatible with Linux and Windows. Supports multiple databases like SQL Server, PostgreSQL, MySQL, and SQLite.
- Performance optimization:. Supports eager and lazy loading to optimize data retrieval, preventing unnecessary queries.
- Automated change tracking. Keeps entity state synchronized with the database, reducing manual coding efforts.
Learn more about EF Core strengths and architecture specifics, and check the best practices of using it in your project.
2. Dapper
Dapper is a lightweight, high-performance micro-ORM designed for developers who need direct SQL control while benefiting from object mapping. Being listed as the best orm for C# by many developers, this solution provides simple yet powerful data access capabilities without the overhead of a full-fledged ORM.
Key features:
- Performance-focused. One of the fastest ORMs, ideal for high-performance applications with low latency needs.
- Minimal overhead. Lightweight and requires only a few lines of code to execute queries.
- Raw SQL control. Allows direct execution of SQL queries and stored procedures, offering complete database flexibility.
- Advanced query handling. Supports multi-mapping, bulk inserts, and batching multiple queries in a single call.
- Asynchronous support. Enables efficient execution of database operations with async/await patterns.
3. NHibernate
NHibernate is a mature and highly flexible .NET ORM that is widely used in enterprise applications. This solution offers advanced mapping capabilities, extensive customization options, and support for multiple databases. However, it has a steep learning curve and lacks documentation.
Key features:
- Advanced Mapping Capabilities: Supports complex object-relational mappings with fine-grained control.
- Database Flexibility: Works with multiple databases and supports various ID generation strategies (Identity, Sequence, etc.).
- Caching Mechanisms: Includes first- and second-level caching for optimized performance.
- Unit of Work Implementation: Ensures efficient transaction handling and data consistency.
- Mature Ecosystem: Well-established with a strong enterprise presence, offering stability and reliability.
Explore the detailed comparison between NHibernate and EF Core, two leading object-relational mapping frameworks.
4. Marten
Marten is a powerful .NET ORM built specifically for PostgreSQL, offering a hybrid approach that combines traditional relational database features with NoSQL-style document storage. It simplifies schema management and is ideal for applications that require JSON document storage, event sourcing, and full-text search.
Key Features:
- JSON document storage. Leverages PostgreSQL’s advanced JSON capabilities for flexible data modeling.
- Event sourcing support. Provides built-in event store functionality for CQRS-style architectures.
- Hybrid persistence. Supports relational, document, and key/value storage within the same database.
- Optimized querying. Compiled queries offer superior performance compared to traditional ORM LINQ translation.
- Flexible schema management. Reduces the need for complex mapping and database migrations.
5. LinqConnect
LinqConnect by Devart is a powerful ORM for .NET designed to extend the functionality of LINQ to SQL. It offers comprehensive ORM capabilities with native support for SQL Server, Oracle, MySQL, PostgreSQL, and SQLite.
Key features:
- LINQ Provider. Unlike most ORMs, LinqConnect is designed as a LINQ provider, which ensures higher performance and better LINQ support without extra layers between LINQ and SQL.
- Flexible development approaches. Supports code-first, database-first, model-first, and combinations of database-first and model-first.
- Wide integration. Seamlessly integrates with various Microsoft technologies, including Windows Forms, ASP.NET WebForms, WPF, and WCF RIA Services. It also supports LinqDataSource for ASP.NET web applications and data binding for Windows Forms and WPF.
- Mapping support. Supports complex types, many-to-many associations, inheritance (TPT, TPH).
- Rich runtime features:
- Smart Change Tracking for better data consistency.
- Advanced Error Handling for easier troubleshooting.
- Extensibility for customizing CRUD operations and more.
- POCO Support for a clean and flexible domain model.
- Lazy & Eager Loading can be customized on a per-query basis.
- Performance Optimizations. Offers compiled query caching, batch updates, and other performance improvements that ensure faster execution times with minimal code changes.
6. RepoDB
RepoDB is a hybrid ORM for .NET that combines Dapper’s flexibility with the automation of Entity Framework Core. It offers both raw SQL execution for performance and simplified CRUD operations to reduce boilerplate code.
Key Features:
- Hybrid approach. Mixes micro-ORM efficiency with full-ORM capabilities.
- Optimized performance. Lightweight, fast, and memory-efficient for high-speed data processing.
- Asynchronous operations. Supports async CRUD, queries, and transactions.
- Flexible querying. Provides both method-based operations and direct SQL execution.
- Advanced mapping. Includes type mapping, field mapping, and multiple result set mapping.
- Caching & tracing. Features built-in MemoryCache for second-level caching and query tracing.
- SQL statement builder. Simplifies query generation for better maintainability.
7. OrmLite
OrmLite is a lightweight, high-performance ORM designed to simplify data access while maintaining flexibility. It focuses on minimal configuration, safety, and high efficiency, making it a great choice for developers who want control over SQL while avoiding excessive boilerplate code.
Key features:
- Bulk inserts. Efficiently insert large datasets with optimized performance.
- Reference support. Easily define relationships between entities.
- Typed join expressions. Enables strongly-typed LINQ-style joins.
- Dynamic result sets. Retrieve flexible, dynamic data structures.
- Database transactions. Supports ACID-compliant transaction management.
- Type converters. Custom serialization for complex data types.
8. PetaPOCO
PetaPoco is a lightweight and high-performance micro-ORM for .NET designed for simplicity, speed, and flexibility. It took best from multiple ORMs while maintaining minimal overhead and zero dependencies.
Key features:
- Tiny & fast:. Uses dynamic method generation (MSIL) for quick property assignments.
- Async & sync support. Perform database operations asynchronously or synchronously.
- Pure POCOs. Works with undecorated POCOs or attributed POCOs for flexibility.
- Fluent configuration. Easy setup without extensive boilerplate.
- CRUD helper methods. Built-in Insert, Delete, Update, Save, and IsNew methods.
- SQL-first approach. Directly write SQL queries without ORM overhead.
- SQL Bbuilder:. Low-friction SQL helper for inline query writing.
- Logging & customization. Hooks for exception logging, value converters, and custom mappings.
- Wide database compatibility. Supports SQL Server, SQLite, MySQL, PostgreSQL, Firebird, MariaDB, MS Access, and more.
- Cross-platform. Works with .NET Standard 2.0, .NET 4.0/4.5+, and Mono 2.8+.
9. XPO
XPO is a blazing-fast ORM for .NET designed for code-centric development with minimal database complexity. It supports Code-First, Model-First, and Database-First workflows, making it a versatile choice for .NET developers.
Key features:
- High performance. Optimized for speed, allowing efficient data retrieval and persistence.
- Transparent object-relational mapping. Uses .NET Reflection and attributes to map business objects to relational databases.
- CRUD & Query support. Supports LINQ queries, object queries, and calculated conditions for flexible data retrieval.
- Built-in caching. Uses MemoryCache for enhanced performance.
- Transaction & concurrency support. Implements Unit of Work, optimistic locking, and nested transactions for data consistency.
- Binding & pagination. Simplifies UI development by binding paginated object collections to controls.
- Multi-database support. Compatible with SQL Server, MySQL, PostgreSQL, Oracle, SQLite, Firebird, and more.
- Custom constraints & indexes. Allows developers to define custom constraints and database indexes using metadata attributes.
Comparison
.NET ORM frameworks tend to have different strengths and specifics that make them totally fit one project and use case and be inapplicable for a different instance. Since it might be difficult to get them compared, check the table below to find the best ORM for .NET project you are handling.
| Product | Type | Support for SQL | Database Support | Model-First or Code-First | Performance Optimization |
|---|---|---|---|---|---|
| Entity Framework Core (EF Core) | Full-ORM | LINQ + SQL | SQL Server, PostgreSQL, MySQL, SQLite, etc. | Both (Code-First, Database-First, Model-First) | Second-Level Cache, Lazy Loading, Compiled Queries |
| Dapper | Micro-ORM | Raw SQL | SQL Server, MySQL, PostgreSQL, etc. | Code-First | Minimal overhead, high performance for raw SQL |
| NHibernate | Full-ORM | HQL, LINQ | SQL Server, MySQL, PostgreSQL, etc. | Both (Code-First, Database-First, Model-First) | Second-Level Cache, Lazy Loading, Optimized for large datasets |
| Marten | Full-ORM | LINQ + SQL | PostgreSQL | Code-First | Optimized for event sourcing, eventual consistency |
| LinqConnect | Full-ORM | LINQ-based | PostgreSQL, SQL Server, MySQL, SQLite | Both (Code-First, Database-First, Model-First) | Compiled query cache, batch updates |
| RepoDB | Hybrid-ORM | Raw SQL | SQL Server, MySQL, PostgreSQL, etc. | Code-First | Batch updates, high performance, optimized SQL execution |
| OrmLite | Micro-ORM | Raw SQL + POCO Support | SQL Server, PostgreSQL, MySQL, SQLite | Code-First | Memory caching, fast CRUD operations |
| PetaPoco | Micro-ORM | Raw SQL + POCO Support | SQL Server, PostgreSQL, MySQL, SQLite | Code-First | Memory caching, high performance, optimized for raw SQL |
| XPO | Full-ORM | LINQ + SQL | SQL Server, MySQL, PostgreSQL, SQLite, Oracle, etc. | Both (Code-First, Database-First, Model-First) | Compiled queries, batch updates, caching |
Best practices for using ORMs in .NET
On your quest to find the best ORM for .NET Core, you might already have some options in mind. However, having a perfect ORM doesn’t mean you will build a scalable and sustainable app at the end of the day. There are certain pitfalls in relying on ORMs just a bit too much or overusing them when it’s not that necessary. The focal point of using an ORM for .NET is that it should help you keep things simple, efficient, and flexible as you map objects to relational data. However, sometimes, this isn’t the case. Here’s how you can get the most out of your ORM solution, ensuring clean, performant, and easy-to-maintain code.
1. Keep things simple
Complex configurations or additional steps (like source code generation) can add overhead, increase maintenance, and make the ORM harder to use. A good ORM should be intuitive and not require complex configurations, preprocessing, or code generation. Minimize unnecessary steps, such as creating many additional files for mappings or configurations. This ensures that the ORM actually improves productivity instead of creating new headaches.
2. Non-intrusive object model
Many ORMs impose certain rules or require special classes (e.g., base classes or proxy objects) that make it harder to integrate the ORM into your existing object model. Use POCOs (Plain Old CLR Objects) for your business logic. Avoid requiring any superclasses or proxies in your object models. This keeps your objects clean and focused solely on business logic without introducing unnecessary dependencies on the ORM.
3. Flexibility in object modeling
Some ORMs impose limitations on how you model your domain, such as restricting class relationships or requiring you to flatten models. Your ORM should allow you to model your domain as you see fit, supporting class hierarchies, relationships (one-to-one, one-to-many), and operations (lazy loading, deep fetching). The ORM should not impose restrictions on your business logic.
4. Declarative and simple mapping
Mapping between the object model and the database schema can get messy and complicated if not organized properly. It can also increase maintenance overhead when mappings are embedded in code. Keep your mappings clear and easy to manage. Avoid putting mappings directly in your source files, as it clutters your code and requires constant recompilation. Instead, store mapping specifications externally, in a simple, declarative format like XML or annotations, but without overloading the system.
5. Control object modicications
Automatically persisting changes to the database can lead to unintended data loss or corruption, as you might not want all changes to be saved. Avoid making assumptions about the persistence of an object. Developers should explicitly control when an object is updated, inserted, or deleted. This ensures the ORM doesn’t unintentionally modify data that wasn’t meant to be persisted.
6. Avoid overly complex query languages and APIs
Some ORMs introduce complex query languages or APIs that can be cumbersome to use and difficult to understand. SQL is powerful and widely understood, so leverage its capabilities through LINQ or raw SQL queries. This makes it easy to work with.
7. Use direct database access when needed
While the ORM should handle most tasks, you may ыешдд need direct access to the database. For such cases, provide simple mechanisms for executing raw SQL queries without complicating the ORM interface.
Enhancing ORM with Devart tools
Devart offers a suite of tools that significantly enhance the capabilities of ORM in .NET, particularly for PostgreSQL databases.
Entity Developer
Entity Developer is a powerful ORM designer for ADO.NET Entity Framework, NHibernate, LinqConnect, Telerik Data Access, and LINQ to SQL. It simplifies the design, development, and maintenance of ORM models through its visual designer and code generation capabilities. For PostgreSQL, Entity Developer ensures that developers can use the full power of their ORM with enhanced productivity and reduced development time.
dotConnect
dotConnect is an enhanced ORM-enabled data provider that builds on the ADO.NET technology. It supports a vast range of ORM solutions, including Entity Framework, NHibernate, and LinqConnect. dotConnect enhances ORM performance with your databases by providing advanced features such as secure SSL connections, PostgreSQL notifications, PostgreSQL bulk data loading, GEOMETRY, PostgreSQL ARRAY types, and others.
Conclusion
When choosing the best ORM for .NET, remember that there’s no one-size-fits-all solution. Each ORM brings its own set of strengths and trade-offs, whether it’s code-first, model-first, or database-first approaches. What’s most important is finding the one that aligns with your development philosophy and project needs.
Using an ORM for .NET projects, when done right, reduces bugs, enhances security, and simplifies maintenance, but the choice of the ORM is only the first step to successful app development. Make this choice wisely based on your project’s specifics, and use the best practices of object-relational mapping for top results and balanced performance.
Also, having an ORM designer to complete your toolset might also help you with faster, mistake-free development.
Check Entity Developer from Devart to learn how to combine it with EF Core, NHibernate, and other popular ORMs to design ORM models faster.
