How to Set Up dbt Cloud to Rockset

Learn how to create an account on GitHub for Rockset setup with dbt Developer Hub. Access and manage the dbt-Rockset adapter for seamless integration.
Published
May 10, 2024
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How can I set up Rockset with dbt Developer Hub?

Setting up Rockset with dbt Developer Hub is a straightforward process. According to dbt Docs, the dbt-Rockset adapter 2.0 supports all four core dbt materializations. To get started, you need to create an account on GitHub and then use pip3 to install dbt-rockset. Configuration is the next step.

  • GitHub Account: This is the first step in setting up Rockset with dbt Developer Hub. GitHub is a platform where developers can collaborate on projects. You will need an account to access the dbt-Rockset adapter.
  • Installation: After creating your GitHub account, the next step is to install dbt-rockset. This can be done using pip3, a package installer for Python.
  • Configuration: Once dbt-rockset is installed, you need to configure it to work with your specific setup. The configuration process will vary depending on your specific needs.

What are the core dbt materializations supported by dbt-Rockset adapter 2.0?

The dbt-Rockset adapter 2.0 supports all four core dbt materializations. These materializations are the ways in which dbt models can be transformed into database objects. They include tables, views, incremental models, and ephemeral models.

  • Tables: These are the most basic form of database object. They store data in rows and columns.
  • Views: These are virtual tables based on the result-set of an SQL statement.
  • Incremental Models: These are models that only update rows that have changed since the last time the model was run.
  • Ephemeral Models: These are models that are used as intermediate steps in a dbt project. They are not materialized into the database.

Where can I find the dbt-Rockset adapter?

The dbt-Rockset adapter is available on both GitHub and PyPI. GitHub is a platform for developers where you can find the source code for the adapter. PyPI, on the other hand, is a repository for Python software where you can download the adapter for use.

  • GitHub: This is a platform where developers can collaborate on projects. The dbt-Rockset adapter is available here.
  • PyPI: This is a repository for Python software. You can download the dbt-Rockset adapter from here.

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