Model Materializations

Materializations are strategies that determine how dbt™ persists your models in the data warehouse. Think of them as different ways to store and update your transformed data.

Available Materialization Types

Type	Description	Best For
View	A saved query that runs on-demand	Simple transformations, real-time data needs
Table	A physically stored copy of your data	BI tools, complex queries, frequent access
Incremental	A table that updates only new/changed data	Large datasets, frequent updates
Ephemeral	Code that’s injected into dependent models	Large datasets, frequent updates

If you don’t specify a materialization, dbt™ will create your model as a view by default.

Configuring Materializations

You can configure materializations in two ways:

1. Project Level (dbt_project.yml)

dbt_project.yml

models:
  your_project:
    finance:
      +materialized: table    # All finance models as tables
    staging:
      +materialized: view     # All staging models as views

2. Model Level (in .sql files)

{{ 
  config(
    materialized='table'
  )
}}

select * from ...

Choosing the Right Materialization

Consider these factors when selecting a materialization:

Factor	Consideration
🔄 Data Freshness	How current does the data need to be?
⚡ Query Performance	How current does the data need to be?
📊 Data Volume	How much data are you transforming?
💰 Resource Cost	What are your compute/storage constraints?

Learn more about each materialization type in their dedicated documentation pages:

​Available Materialization Types

​Configuring Materializations

​1. Project Level (dbt_project.yml)

​2. Model Level (in .sql files)

​Choosing the Right Materialization

Available Materialization Types

Configuring Materializations

1. Project Level (dbt_project.yml)

2. Model Level (in .sql files)

Choosing the Right Materialization