dbt vs Apache Airflow

-- models/marts/fct_orders.sql
WITH orders AS (
    SELECT * FROM {{ ref('stg_orders') }}
),
customers AS (
    SELECT * FROM {{ ref('stg_customers') }}
)
SELECT
    o.order_id,
    o.order_date,
    c.customer_name,
    o.total_amount
FROM orders o
JOIN customers c ON o.customer_id = c.customer_id

-- dbt run --select fct_orders
-- dbt test --select fct_orders

from airflow import DAG
from airflow.operators.python import PythonOperator
from datetime import datetime

with DAG('etl_pipeline',
         start_date=datetime(2024, 1, 1),
         schedule_interval='@daily') as dag:

    extract = PythonOperator(
        task_id='extract',
        python_callable=fetch_from_source
    )
    transform = PythonOperator(
        task_id='transform',
        python_callable=clean_and_model
    )
    load = PythonOperator(
        task_id='load',
        python_callable=write_to_warehouse
    )

    extract >> transform >> load