Changelog

All databases with direct connect now supported in User Connections

Allocate AI credits across users from a shared organizational pool, with visibility into assigned, consumed, and remaining balances.

Route account-level notifications to Slack for team visibility while maintaining security alerts via email.

Design a governed, AI-ready semantic layer directly alongside their physical model and forward-engineer it into Snowflake Semantic YAML

The SqlDBM Copilot Context Folder processes uploaded files (Excel, CSV, SQL, Images, PDF) to extract and analyze data models, DDL, documentation, and diagrams.

The SqlDBM Copilot now adds AI-generated summaries to the Compare Revisions and Forward Engineering screens.

Your data model, now readable by AI. The model your team built in SqlDBM becomes the source of truth your AI reads its context from.

Auto-generate Snowflake views and tables from YAML templates, reducing SQL effort from hours to seconds.

Full support for ARRAY and RANGE types (including arrays of structs), property-level Compare that goes beyond plain-text diffing, and editable columns and descriptions on views.

Views now support Virtual Primary Keys and Virtual Business Keys

Forward Engineering now adds quick-filters to instantly isolate dbt sources and models

Snowflake Excel upload support for Dynamic, Hybrid and Iceberg tables

Views and Dynamic Tables now support visible, editable data types as metadata

For automated, system-driven project changes

Redshift news and native syntax support

SqlDBM now supports database.schema.object naming for greater modeling precision.

You can now group projects into dashboard folders with unlimited nesting.

Uploading a dbt manifest now creates virtual dependency relationships from dbt refs.

Connect physical objects back to logical models.

Embed documentation anywhere.

Bridge the gap between your data models and dbt projects with dbt Manifest Import

Model logical joins and data lineage with new virtual relationships

The FE screen is now more streamlined and intuitive

Improved auto-layout, snap-to-grid, alignment guides, and full line reshaping!

Fine-tune word boundaries for control over underscores, numbers, and case changes

FK linking respects column position, and Explorer menus allow Shift+Click multi-select

An AI data modeling assistant that supercharges your productivity

Migrate objects, diagrams, and subject areas from ERwin to SqlDBM

Support for select-all (Ctrl+A) and multiselect (Shift+click) on columns

Flag objects to ignore naming, case, or glossary rules

Iceberg, Dynamic, and Hybrid tables supported in Database Documentation and compare

Fields and Pages editing and merging in Concurrent Working branches

Full native support for all catalog types and properties

Full native support for all properties and indexes

Full native support for Dynamic tables, their logic, and properties

Exclude items from Global Reference at object or schema level

Drag-and-drop functionality for objects in Diagram Explorer

Cancel/reselect revisions mid-compare and schema filtering on Database Documentation

Map predefined standards to your existing projects

Navigable links can now be included alongside your objects

Model Governance fields are now easily accessible directly from the diagram

View existing relationships among global objects without needing to navigate away from the local project

Performance and visual improvements using properties instead of text

Apply rules to physical and/or logical names or set inactive

Case standards for logical names

iFrame embeds for projects in third-party systems

Snowflake views on the diagram with editable columns and parameters

Enhanced foreign key linking experience

Snowflake revamped object parser offers faster performance

Push dbt source & model YAML to git in Forward Engineering

Added support for multiple repos in push-to-git

Simplified UI for Foreign Keys and Relationships