Materializations (view, table, incremental, ephemeral) in dbt - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a view materialization in dbt?

A view materialization creates a virtual table in the database. It does not store data physically but runs the query every time you access it, like a saved question you ask repeatedly.

beginner

How does a table materialization differ from a view in dbt?

A table materialization creates a physical table in the database. It stores the data permanently until refreshed, so queries run faster because data is precomputed.

intermediate

What is the purpose of incremental materialization in dbt?

Incremental materialization updates only new or changed data in a table instead of rebuilding the whole table. This saves time and resources when working with large datasets.

intermediate

Explain ephemeral materialization in dbt.

Ephemeral materialization does not create any table or view. Instead, it inlines the SQL code into downstream models. It's like a temporary helper used only during query execution.

intermediate

When should you use incremental materialization instead of table materialization?

Use incremental when your data updates regularly but only a small part changes each time. It speeds up processing by adding or updating just new data, not rebuilding everything.

Which dbt materialization creates a virtual table that runs the query every time you access it?

A View

B Table

C Incremental

D Ephemeral

A view materialization creates a virtual table that runs the query on demand.

What does table materialization do in dbt?

A Creates a temporary inline SQL snippet

B Creates a physical table storing data

C Updates only new data

D Creates a virtual table without storing data

Table materialization creates a physical table that stores data permanently.

Which materialization is best for large datasets that update incrementally?

A View

B Table

C Incremental

D Ephemeral

Incremental materialization updates only new or changed data, saving time.

What happens with ephemeral materialization in dbt?

A Inlines SQL code into downstream models

B Creates a physical table

C Creates a view

D Updates data incrementally

Ephemeral materialization inlines SQL code and does not create tables or views.

Why choose incremental over table materialization?

A To inline SQL code

B To store data permanently

C To create a virtual table

D To update only new or changed data

Incremental materialization updates only new or changed data, improving efficiency.

Describe the four types of materializations in dbt and when to use each.

Think about how data is stored or updated in each type.

Explain how incremental materialization improves performance compared to full table rebuilds.

Consider what happens when you update a big table fully versus partially.