Release Notes

August 2026

We've updated the following quickstart data model packages to add DuckDB as a supported destination:

June 2026

v0.4.0

Under the Hood

• Migrates the union_connections, apply_source_relation, and partition_by_source_relation macros to the dbt_fivetran_utils package.
• Adds the fivetran_using_source_casing variable for case-sensitive destination support. When enabled, downstream transformations respect source casing to ensure consistent results. See the Additional Configurations section of the README for details.

March 2026

v0.3.2

Documentation

• Updates column descriptions for line_item_line_item_type and related fields to be more concise.
• Updates README to remove badges and replace with plain-text dbt Core version compatibility.

Under the Hood

• Adds a persist_docs conditional to integration tests to enable relation and column documentation persistence, except for Databricks targets.

January 2026

v0.3.1

Under the Hood

• Adjusts the data type of aws_cloud_cost_start_date in the quickstart.yml from string to date.

v0.3.0

Documentation

• Updates README with standardized Fivetran formatting.

Under the Hood

• In the quickstart.yml file:
  • Adds supported_vars for Quickstart UI customization.

v0.2.0

Features

• Increases the required dbt version upper limit to v3.0.0

Under the Hood

• Updates the README and integration tests architecture to align with other packages

September 2024

v0.1.0

This is the initial release of the aws_cloud_cost dbt package!

📣 What does this dbt package do?

This package models AWS Cloud Cost data from Fivetran's AWS Cost Report connector. It uses data in the format described by the AWS Cost & Usage Report.

The main focus of the package is to transform the core object tables into analytics-ready models, including:

• Materializes AWS Cloud Cost staging tables which leverage data in the format described by the AWS Cost & Usage Report. These staging tables clean, test, and prepare your AWS Cloud Cost data from Fivetran's connector for analysis by doing the following:
  • Names columns for consistency across all packages and for easier analysis:
    • Column names are shortened for convenience and to avoid redundancy.
  • Takes the latest export of each account's billing month report.
• Creates analytics-ready end models for monitoring and investigating cost & usage of different AWS services across your organizations.
• Generates a comprehensive data dictionary of both your AWS Cloud Cost source and modeled data through the dbt docs site.

This package does not apply freshness tests.

The following table provides a detailed list of all models materialized within this package by default.

TIP: See more details about these models in the package's dbt docs site.