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dbt support for database features which are not yet supported natively in dbt-core

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dbt Labs: Experimental Features

This repository includes projects that extend of existing dbt features, experiment with new database features not yet natively supported in dbt, or otherwise demonstrate cool stuff you can do with just Jinja macros in your project—no forks necessary.

In all cases, these are demo projects, not intended as ready-to-use packages. If you want to use code from this repository in your own project, you're more than welcome to clone and install as a local package, or just copy-paste :)

This project adds support for materialized_view as a new dbt materialization. It includes implementations for Postgres, Redshift, Snowflake, and BigQuery, through a mix of new macros and overrides of built-in dbt macros. See the project README for details. For another take on dbt + materialized views, check out the dbt-materialize plugin.

This lab demonstrates a number of options for lambda views, as discussed in this discourse article. Additional details about the various approaches can be found in at lambda-views/README.md.

This lab demonstrates how to use snapshots to detect dbt model regressions, as discussed in this discourse article. Additional details on how to test this code for yourself can be found at snapshot-testing/README.md.

This lab demonstrates how to implement dynamic data masking on Redshift.

Check out this discourse article for more information.

This lab demonstrates two strategies for measuring Time on Task.

Check out this devhub article for more information.

Resources:

  • Learn more about dbt in the docs
  • Check out Discourse for commonly asked questions and answers
  • Join the chat on Slack for live discussions and support
  • Find dbt events near you
  • Check out the blog for the latest news on dbt's development and best practices

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dbt support for database features which are not yet supported natively in dbt-core

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