ORM
An ORM (Object-Relational Mapping) maps database tables to objects in a programming language and replaces SQL with object-oriented methods.
Object-Relational Mapping (ORM) bridges the gap between object-oriented code and relational databases. Instead of writing SQL by hand, developers work with objects and methods in their language. The ORM translates these operations into SQL. Well-known ORMs like Prisma, TypeORM, Hibernate and Django ORM are standard in modern software development.
What is ORM?
ORM is a technique that creates a virtual data layer between application and database. Each table is mapped to a class (entity/model), each row to an object instance and each column to a property. Relationships (1:1, 1:n, n:m) are represented by object references. The ORM generates the corresponding SQL (SELECT, INSERT, UPDATE, DELETE) and handles connection pooling, transactions and mapping results back to objects. Many ORMs also provide schema migrations, validation and type-safe query builders. Popular ORMs include Prisma and TypeORM for TypeScript, Hibernate for Java, Entity Framework for C#/.NET and Django ORM for Python.
How does ORM work?
Developers define data models as classes or schema files that describe table structure. The ORM generates migrations that create or update the database schema. At runtime it translates method calls like user.findMany({ where: { active: true } }) into SQL. Results are mapped to typed objects. Lazy loading loads related data on access; eager loading loads it upfront. Query builders allow complex queries beyond simple CRUD.
Practical Examples
Prisma in TypeScript: Type-safe ORM with declarative schema, automatic migrations and generated client. Ideal for Next.js and NestJS.
Hibernate in Java: Enterprise ORM with JPA, caching, lazy loading and rich mapping for complex domains.
Django ORM in Python: Built-in ORM with QuerySet API, automatic migrations and admin generation.
Entity Framework in C#: Microsoft’s ORM for .NET with LINQ and Azure integration.
TypeORM in TypeScript: Decorator-based ORM supporting both Active Record and Data Mapper patterns.
Typical Use Cases
CRUD applications: Standard database operations are implemented faster and more safely with an ORM
Rapid prototyping: Schema definitions and automatic migrations speed up early development
Type-safe database access: ORMs like Prisma generate typed clients that catch errors at compile time
Multi-database support: An ORM abstracts the database so switching from MySQL to PostgreSQL is minimal
Team productivity: Developers work with familiar OOP syntax without deep SQL knowledge
Advantages and Disadvantages
Advantages
- Productivity: Less boilerplate, faster development with object-oriented syntax instead of raw SQL
- Type safety: Modern ORMs like Prisma offer full type support and autocomplete
- SQL injection protection: ORMs parameterize queries and protect against SQL injection
- Portability: Changing database requires minimal code change because the ORM abstracts SQL dialects
- Migrations: Schema changes are versioned and can be applied reproducibly across environments
Disadvantages
- Performance overhead: Generated SQL is often less optimal than hand-written for complex queries
- N+1 problem: Without careful eager loading the ORM can issue many extra queries
- Abstraction leaks: For complex queries the ORM hits limits and developers fall back to raw SQL
- Learning curve: Each ORM has its own API and conventions
Frequently Asked Questions about ORM
When should I use an ORM and when raw SQL?
What is the N+1 query problem?
Which ORM is best for TypeScript?
Related Terms
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