Analytics Engine PoC: FastAPI vs Flask

This proof-of-concept compares performance and integration between Flask and FastAPI using two different backends:

• Apache DataFusion (in-process SQL engine over Parquet)
• PostgreSQL (traditional RDBMS)

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🔧 Run Locally

1. Create and Activate Virtual Environment

virtualenv --python=$(which python3.10) .venv
source .venv/bin/activate

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2. Install Dependencies

pip install -r requirements.txt

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3. Create .env File and Export Variables

Create a .env file with the following content:

export DB_NAME="test"
export DB_USER="admin"
export DB_PASSWORD="admin"
export DB_HOST="localhost"
export DB_PORT="5432"

Then load the environment variables:

source .env

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4. Start PostgreSQL

You can either:

• Run a local PostgreSQL instance manually, or
• Use Docker (see Docker section below)

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5. Seed Dummy Data to Database

pytest tests/test_query_engine.py -s -k test_setup_db

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6. Run FastAPI App Locally

PYTHONPATH=. uvicorn fastapi_app.app:app --reload

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7. Run Flask App Locally

PYTHONPATH=. python flask_app/app.py

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🐳 Run with Docker Compose

1. Build and Run the Stack in Detached Mode

docker compose up --build -d

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• Flask app is exposed on http://localhost:3000
• Fast api is exposed on http://localhost:3001
• PostgreSQL runs inside the analytics_db container

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For load test used apache benchmark

ab -n 10000 -c 200 -l http://localhost:3001/datafusion