Ephemeral Materialization

Unlike other materializations, ephemeral models don’t create database objects. Instead, dbt incorporates the model’s code into dependent models using Common Table Expressions (CTEs). This means:

No physical tables or views are created
Code is integrated into downstream models
Logic can be reused across models

Ephemeral models are ideal for lightweight, reusable transformations that don’t need to be queried directly.

Working with Ephemeral Models

Let’s understand ephemeral models through a simple example:

-- models/intermediate/clean_customer_data.sql
{{
    config(
        materialized='ephemeral'
    )
}}

SELECT
    customer_id,
    TRIM(first_name) as first_name,
    TRIM(last_name) as last_name,
    LOWER(email) as email
FROM {{ ref('raw_customers') }}

When this model is referenced:

No table or view is created
The code becomes a CTE in downstream models
The logic is recomputed each time it’s used

When to Use Ephemeral Models

Ephemeral models work best for:

Simple transformations (cleaning, filtering)
Early-stage models in your DAG
Light data preparation steps
Code that supports 1-2 downstream models

Configuration

Model-Level Configuration

-- In your model SQL file
{{
    config(
        materialized='ephemeral'
    )
}}

SELECT 
    user_id,
    CASE 
        WHEN age < 18 THEN 'youth'
        WHEN age < 65 THEN 'adult'
        ELSE 'senior'
    END as age_category
FROM {{ ref('raw_users') }}

Performance and Usage Guidelines

Advantages and Limitations

Advantages	Limitations
🧹 Reduces database clutter	🚫 Can’t query directly
♻️ Enables code reuse	⚠️ No model contracts support
📦 No storage overhead	🔍 Harder to debug
🔄 Flexible logic updates	🛠️ Limited operational use

When to Change Materialization Consider a different materialization when you:

Need to query the model directly
Have complex transformations
Support many downstream models
Require model contracts

Best Practices

Keep It Simple: Use for lightweight transformations only
Limit Dependencies: Best for 1-2 downstream models
Consider Debugging: Use sparingly to maintain query clarity

Ephemeral models are powerful for code organization but should be used judiciously. Consider views or tables for more complex or widely-used transformations.