Skip to content

10.0 Maintenance Updates

This article lists maintenance fixes and updates for supported DataForge versions.

DataForge Version 10.0

  • February 19, 2026
  • Prevented manual attribute recalculation from trying to run if attempted when there are no rules or no inputs with data
  • Put in fix for converting to unity failures when data types don't match.
    • Custom Refresh sources: if failed, you will need to
    • Other Refresh type sources: if failed, conversion will continue but enr_ table will be left blank
  • Fixed schema name reference for processing when db schema is customized
  • Added fix for unity views being updated to point to different hub tables
  • January 22, 2026
  • Fixed CDC reset on legacy hive source with key and custom refresh from dropping hub table
  • Fixed hive loopback using wrong catalog based on two part naming rather than three part naming select
  • Fixed cleanup from deleting virtual output views when view_schema is defined
  • January 21, 2026
  • Fixed Unity conversion failing for custom refresh source
  • Fixed hyperlink for source hub view name in source settings trying to open wrong schema
  • Fixed virtual output from ignoring 'View database' parameter and writing to project schema name
  • Fixed Convert to Unity from not working for sources that are established but have no data
  • Fixed loopback from looking at the wrong schema
  • Added auto-detect Java21 path and Max RAM during Agent MSI install
  • Fixed Unity source from missing step in Refresh to create/update source hub view if it is changed
  • January 8, 2026
  • Update Deployment App for Snowflake
    • Updated the deployment application to interact directly with Snowflake objects, ensuring upgrades and maintenance workflows run correctly in Snowflake-based environments.
  • Update Terraform Scripts for SaaS
    • Improved SaaS deployment configuration to support both Databricks and Snowflake by allowing the lakehouse platform to be explicitly selected and removing Databricks‑only assumptions.
  • Snowflake Platform Support
    • Added native Snowflake processing support so DataForge can operate consistently across Snowflake and Databricks environments.
  • Add Snowflake Processing to Core Engine
    • Extended the core processing engine to run Snowflake workloads using the same architectural patterns as existing Databricks deployments.
  • Snowflake UI Updates
    • Updated user interface terminology and workflows for Snowflake deployments, including renaming “Cluster” to “Compute” for improved clarity.
  • Add Local Agent to Snowflake Environments
    • Added support for running a local agent in Snowflake environments, including required networking, task services, and secure authentication setup.
  • Deprecate Client/Environment Name Usage in Upgrade API
    • Improved upgrade reliability by removing reliance on client or environment display names and instead using stable internal identifiers.
  • Fix Missing Compute Header
    • Resolved a UI issue where the Compute header was not displayed in certain views.
  • Snowflake SDK Availability
    • Made the DataForge SDK available through Snowpark, enabling easier development and execution of integrations directly within Snowflake.
  • Optimize Hub Table Validation
    • Improved hub table schema validation to be more accurate and resilient during processing.
  • Improve Dependency Page Dark Mode Colors
    • Enhanced contrast and readability for pagination and UI elements in dark mode on the Dependencies page.
  • Improve Source Validation Errors
    • Refined validation logic and error messaging to make source configuration issues easier to understand and resolve.
  • Fix Deployment Permission Errors
    • Resolved an issue where deployments could fail due to library allowlist and permission restrictions.
  • Improve Snowflake Environment Provisioning
    • Streamlined provisioning steps for Snowflake environments to improve reliability and reduce setup friction.
  • Improve Upgrade Stability
    • Addressed edge cases in upgrade workflows to reduce the risk of failed or partial upgrades.
  • UI Performance Improvements
    • Made general performance and responsiveness improvements across several UI pages.
  • Improve Error Handling for Failed Tasks
    • Enhanced error handling and reporting for failed tasks to make troubleshooting easier.
  • Improve Metadata Consistency
    • Improved consistency and accuracy of metadata generated during ingestion and processing.
  • Improve Snowflake Job Execution
    • Optimized Snowflake job execution behavior for better performance and reliability.
  • Fix Dependency Refresh Issues
    • Resolved an issue where dependency refreshes could fail or produce inconsistent results.
  • Improve Logging for Deployments
    • Added clearer logging around deployment steps to improve observability and debugging.
  • Improve Validation for Configuration Changes
    • Strengthened validation checks when applying configuration changes to reduce runtime errors.
  • Fix Edge Cases in Upgrade Rollbacks
    • Addressed rare edge cases that could prevent successful rollback during failed upgrades.
  • General Stability and Bug Fixes
    • Included additional minor fixes and stability improvements across the platform.