Database Fundamentals in Python: What are Databases and Why We Need Them

Every day we use dozens of applications: checking social media, shopping online 🛒, listening to music, booking tickets ✈️. Behind each of them is a database — a system that instantly finds the right information among millions of records.

Databases are the fundamental technology of modern applications. For Python developers, understanding database principles opens doors to creating scalable and reliable solutions.

What is a Database? 🤔

Database (DB) — an organized collection of data that is stored and managed by a specialized system (DBMS).

Simple analogy: a database is like a smart warehouse. Each "shelf" has its own address, and the "warehouse robot" (DBMS) can quickly find and deliver any needed information.

Why Not Store Data in Python Lists? 🤷‍♂️

Let's consider a simple example — storing users:

Python 3.13
# Storage in Python list
users = [
    {"id": 1, "name": "Anna", "email": "anna@example.com"},
    {"id": 2, "name": "Peter", "email": "peter@example.com"},
    # ... imagine a million users here
]

# Search user by email
def find_user_by_email(email):
    for user in users:  # Check the ENTIRE list! 😱
        if user["email"] == email:
            return user
    return None

Problems with this approach:

• Slow search — need to check every user
• Memory limitations — all data must fit in RAM
• Data loss — if the program crashes, everything is lost
• Concurrency — what if multiple users modify data simultaneously?

Databases solve all these problems out of the box — that's why they became the standard for serious applications.

Main Types of Databases

There are many types of databases, but let's highlight the three most important:

1. Relational Databases

Organize data into tables with clear structure. The most popular type.

Python 3.13
-- Example users table
CREATE TABLE users (
    id INTEGER PRIMARY KEY,
    name VARCHAR(100),
    email VARCHAR(150)
);

2. Key-Value Databases

Store simple "key-value" pairs. Very fast for simple operations.

Python 3.13
# Example in Redis — popular key-value DB
user_session = {
    "session:user123": "logged_in",
    "cart:user123": "[1,5,9]",  # Product IDs in cart
    "last_seen:user123": "2024-01-15 10:30"
}

3. Document-Oriented Databases

Store data as documents (JSON format). Flexible structure.

Python 3.13
# Example user document
{
    "name": "Anna",
    "email": "anna@example.com",
    "preferences": {
        "theme": "dark",
        "language": "en"
    }
}

Popular Database Management Systems 🏆

Here's the top-8 most used DBMS in 2024:

1. PostgreSQL — powerful relational DB
2. MySQL — popular relational DB for web
3. SQLite 📱 — lightweight relational DB
4. MongoDB — leader in document-oriented DBs
5. Redis ⚡ — fast key-value DB
6. Oracle Database — enterprise relational DB
7. Microsoft SQL Server — relational DB from Microsoft
8. Elasticsearch — document-oriented search DB

Conclusion: relational databases (5 out of 8 positions) are the industry standard due to their reliability and universality.

What's Next? 🎯

In the next article, we'll start practicing with SQLite — the perfect database for learning, which is already built into Python. You'll create your first DB and learn to work with real data.