## What is ORM?
Object-Relational Mapping (ORM) is a technique that lets you work with databases using your programming language instead of writing SQL. You manipulate objects and classes, and the ORM translates that into SQL queries automatically.
Think of ORM as a translator between your code (objects) and your database (tables and rows).
## The Problem ORMs Solve
Without ORM, you write raw SQL scattered throughout code. This leads to SQL injection risks, no type safety, repetitive boilerplate, and database-specific SQL.
With ORM, you work with objects and methods. The code is cleaner, safer, and easier to read.
## How ORMs Work
You define models (classes) that represent database tables. Each model property maps to a table column. The ORM creates or uses corresponding database tables.
Interact with models, not tables. ORM handles SQL generation automatically.
## Popular ORMs
**JavaScript/TypeScript**: Sequelize, TypeORM, Prisma, Mongoose
**Python**: Django ORM, SQLAlchemy, Peewee
**Java**: Hibernate, JPA
**Ruby**: ActiveRecord
**PHP**: Eloquent, Doctrine
**C#**: Entity Framework
Every language has mature ORM options.
## CRUD Operations with ORM
Create, read, update, and delete operations become simple method calls on model objects.
## Relationships
ORMs handle relationships between tables like one-to-many, many-to-many, and one-to-one. Define relationships in models and the ORM generates the necessary JOIN queries automatically.
## Query Building
ORMs provide fluent APIs for building complex queries with filters, joins, ordering, and limits. The ORM translates these into optimized SQL.
## Migrations
ORMs manage database schema changes through migrations. Track database versions and apply changes consistently across environments.
## Advantages of ORMs
**Productivity**: Write less code, focus on business logic
**Type Safety**: TypeScript ORMs catch errors at compile time
**Database Agnostic**: Switch databases with minimal code changes
**Security**: Prevents SQL injection automatically
**Maintainability**: Cleaner code, easier to understand
## Disadvantages of ORMs
**Performance**: Generated SQL may not be optimal for complex queries
**Learning Curve**: Must learn ORM API in addition to SQL
**Abstraction Leaks**: Complex queries still require raw SQL
**Black Box**: Harder to debug when ORM generates bad queries
**Overhead**: Additional layer between code and database
## When to Use Raw SQL
ORMs are great for most operations, but use raw SQL for complex analytical queries, performance-critical operations, bulk operations, database-specific features, or when ORM makes queries too complicated.
Most ORMs let you drop down to raw SQL when needed.
## N+1 Query Problem
Common ORM pitfall where fetching a list then accessing related data in a loop creates N+1 queries. Solution is eager loading - load related data upfront with joins.
## Best Practices
**Use Migrations**: Never modify database schema manually
**Index Properly**: ORMs do not automatically index - add indexes yourself
**Monitor Queries**: Log generated SQL to catch performance issues
**Lazy vs Eager Loading**: Understand when to load related data
**Connection Pooling**: Configure pool size for your workload
## Modern ORMs
Modern ORMs like Prisma provide excellent developer experience with full type safety, auto-completion, and schema-first development.
## The Bottom Line
ORMs make database interactions cleaner, safer, and more productive. You write less boilerplate, avoid SQL injection, and get type safety.
Learn your ORM well, but also understand SQL. The best developers know both and use each where appropriate. For 90% of database operations, ORMs are the right choice.
