Comparing Snowflake Dynamic Tables with dbt

Snowflake Dynamic Tables are a new type of table that update when their parent table(s) update, useful for modeling where you need the data to be current. dbt is a popular framework for transformations, increasing accessibility and collaboration in modeling through SQL-based modeling and centralized code repositories with documentation history. While Snowflake Dynamic Tables and dbt have similarities such as updating an object based on query results and using SQL as the primary modeling language, there are differences including frequency of updates, modularity, version control, validation rules (tests), and lineage + documentation. Using both tools together can provide the benefits of a git environment for modeling code, built-in lineage and documentation, and automatic updates to models triggered by refreshed data.