What is ORM?

At its essence, ORM acts as a bilingual intermediary between the object-oriented nature of programming languages (like Python, Java, or C#) and the relational structure of databases (such as MySQL, PostgreSQL, or SQL Server). It allows developers to interact with databases using familiar object-oriented principles, abstracting the complexities of SQL queries and database schemas.

Components of ORM

1. Entities/Models

   In ORM parlance, objects in the programming language are typically known as entities or models. These entities reflect the data stored in the database, mirroring its architecture. For instance, in a blogging platform, a "Post" entity might correspond to a "posts" table in the database.

2. Mappings

   ORM frameworks utilize mappings to create links between objects and database tables, as well as between object attributes and table columns. These mappings dictate how data is translated between the two realms. For example, a mapping could indicate that the "title" property of a "Post" object aligns with the "title" column in the "posts" table.

3. Session/Context

   The session or context within ORM acts as a connector between the application code and the database. It provides methods for querying, inserting, updating, and deleting data, abstracting the underlying SQL commands. Developers engage with the session to perform CRUD (Create, Read, Update, Delete) operations on entities.

Example

Let’s look at a straightforward example using Python and SQLAlchemy, a well-known ORM library. Imagine we have a "User" entity representing users in our application.

With ORM, defining this entity is simple:

from sqlalchemy import Column, Integer, String

from sqlalchemy.ext.declarative import declarative_base

Base = declarative_base()

class User(Base):

__tablename__ = 'users'

id = Column(Integer, primary_key=True)

name = Column(String)

age = Column(Integer)

Now we can interact with the "User" entity using ORM methods:

from sqlalchemy import create_engine

from sqlalchemy.orm import sessionmaker

engine = create_engine('sqlite:///example.db')

Base.metadata.create_all(engine)

Session = sessionmaker(bind=engine)

session = Session()

# Creating a new user

new_user = User(name='Alice', age=30)

session.add(new_user)

session.commit()

# Querying users

users = session.query(User).all()

for user in users:

print(user.name, user.age)

In this scenario, ORM manages the translation between Python objects and SQL commands, allowing us to engage with the database using object-oriented syntax.

Resources for Deeper Dives

• Popular ORM options: Your ORM choice will depend on your programming language. Notable options include Hibernate (Java), SQLAlchemy (Python), and Django ORM (Python). More information and tutorials can be found on their respective sites.