Database Choices: SQL vs. NoSQL in FastAPI

FastAPI doesn't care where you store your data. Whether you use a 30-year-old Postgres instance or a cutting-edge MongoDB cluster, FastAPI provides the tools to integrate them cleanly.

However, choosing the right database for your specific use case is the most important decision you will make in the lifecycle of your app.

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1. SQL (Relational) Databases

The "Standard" for most business applications. Examples: PostgreSQL, MySQL, SQLite.

Best For:

• Structured Data: Users, Orders, Inventory.
• Complex Joins: "Find all users who bought product X in category Y."
• ACID Compliance: Ensuring data integrity (crucial for financial apps).

Integration in FastAPI:

We typically use SQLAlchemy or SQLModel (a wrapper around SQLAlchemy designed specifically for FastAPI).

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2. NoSQL (Non-Relational) Databases

Designed for horizontal scale and flexible schemas. Examples: MongoDB, DynamoDB, Redis.

Best For:

• Unstructured Data: Blog comments, product logs, metadata.
• AI Agents: Storing semi-structured state or long-term memory.
• High Velocity: Apps that write thousands of records per second.

Integration in FastAPI:

We typically use Motor (async driver for MongoDB) or Beanie (an ODM built on top of Pydantic).

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3. Sync vs. Async Drivers

FastAPI is an async framework, so to get the maximum performance, you should use Async Database Drivers.

• Sync: The thread blocks while waiting for the database to return data. (Slow for high concurrency).
• Async: The server handles other requests while waiting for the database. (Extreme performance).

Database	Driver (Sync)	Driver (Async)
Postgres	psycopg2	asyncpg / SQLAlchemy Async
SQLite	sqlite3	aiosqlite
MongoDB	pymongo	motor

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4. The Hybrid Approach: Vector Databases

In the era of AI Agents, you often need a third type of database: Vector Databases (e.g., Chroma, Pinecone, Weaviate). These store "Embeddings" (mathematical representations of text) and allow your API to perform semantic searches rather than just keyword lookups.

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Visualizing the Data Layer

graph TD
    A["FastAPI App"] --> B{Database Type?}
    B -- "Relational" --> C["Postgres / SQLModel"]
    B -- "Document" --> D["MongoDB / Beanie"]
    B -- "Search / AI" --> E["Chroma / Pinecone"]
    
    C & D & E --> F["Persistent Storage"]

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Summary

• SQL is for structure and integrity.
• NoSQL is for flexibility and scale.
• Async Drivers are essential to maintain FastAPI's performance.
• SQLModel is the recommended choice for most new FastAPI projects.

In the next lesson, we’ll look at ORM and Query Layers, specifically focusing on how to map your Python classes to database tables.

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Exercise: The Big Choice

Scenario: You are building a Social Media Platform like Twitter.

1. Where would you store the User Profiles (Name, Email, Password)? (SQL or NoSQL?)
2. Where would you store the Global Trending Topics (updated every 30 seconds)?
3. Why did you make those choices?