Version 1.0.62

Released July 30, 2026.

dbt Core

Create a transformation project from scratch or import an existing dbt repository. Transformation projects now support file editing, model preview, compiled SQL, logs, documentation, catalog exploration, and supported dbt Core commands.

Add a transformation project to an orchestration to run dbt after ingestion pipelines and before activation pipelines.

Supported transformation datasources are Snowflake, PostgreSQL, Amazon Redshift, Google BigQuery, and Databricks.

Create a dbt Core transformation project

Git Workflows

Connect your GitHub, GitLab, Azure DevOps, or other Git server account under Settings → Linked accounts. Git-backed transformation projects support diffs, staging, discarding, feature branches, pulls, commits, pushes, and opening a pull request in the linked provider.

The default branch remains read-only in Supaflow. Git actions run only when you start them.

Set up the transformation Git workflow

Databricks Source and Destination

Databricks is now available for ingestion and activation pipelines, dbt Core transformation projects, and SQL Script tasks. Use it as both a source and a destination.

The connector supports OAuth machine-to-machine authentication for production and personal access tokens for testing. Source pipelines discover accessible Unity Catalog tables and views. Destination pipelines load through an existing Unity Catalog volume.

• Configure Databricks as a source
• Configure Databricks as a destination

Google BigQuery Source and Destination

Google BigQuery is now available for ingestion and activation pipelines, dbt Core transformation projects, and SQL Script tasks. Use it as both a source and a destination. Source pipelines can read accessible tables and views. Destination pipelines use a customer-owned Cloud Storage staging bucket.

• Configure Google BigQuery as a source
• Configure Google BigQuery as a destination

Expanded SQL Script Tasks

SQL Script tasks now run on Snowflake, PostgreSQL, Amazon Redshift, SQL Server, Google BigQuery, and Databricks datasources.

Create a SQL Script task

Google Drive Destination

Google Drive destination pipelines can write CSV files, native Google Sheets, or Excel workbooks. Google Sheets and Excel default to one file per object; choose Single Workbook to collect all objects from a pipeline into one workbook. File names use the pipeline and object names so generated output is easier to find.

Configure the Google Drive destination

Snowflake and Redshift Table Settings

When compatible target tables must be recreated, Snowflake preserves clustering definitions and Amazon Redshift preserves supported DISTKEY and SORTKEY settings whose referenced columns still exist.

• Configure the Snowflake destination
• Configure the Amazon Redshift destination

Connector Fixes

• Salesforce discovery now lists queryable objects more consistently and preserves login location coordinates accurately.
• HubSpot association and property-history objects now stay aligned with their parent objects during incremental syncs.

Support

Questions about this release? Contact us at support@supa-flow.io