Works with your stack
SQL Server, Snowflake, PostgreSQL, Microsoft Fabric, and more. ADL doesn't care where your data lives. Define connections to any platform, write or pick the templates that target it, and the same captured design can ship to any of them.
Why this matters
Few organizations live on a single platform. Most run a mix — a SQL Server warehouse from years ago, a Snowflake migration in progress, a Microsoft Fabric pilot, a PostgreSQL operational store. Most code-generation and modeling tools pick a side: they're for one platform and treat the others as second-class.
The result is fragmentation. A team standardizes on one tool for Snowflake and ends up with a different tool — different metadata, different conventions, different team workflow — when they take on a SQL Server project. The cost shows up in onboarding, in inconsistent design, and in the friction of moving people between projects.
How ADL delivers
The mechanism is straightforward: ADL's metadata model is platform-neutral. The platform commitment lives in the templates and connections, not in the design itself.
- Data Connections name the target platform. A Data Object belongs to a Data Connection — SQL Server, Snowflake, PostgreSQL, Fabric, or anywhere else. The same design can target multiple connections in the same project.
- Templates are written per platform when they need to be. SQL Server-specific stored procedures live in SQL Server templates; Snowflake views in Snowflake templates. Both pull from the same underlying metadata. If you write a new template for a new platform, the rest of your design doesn't change.
- Starter solutions ship across platforms. Each major methodology (Data Vault, Persistent Staging) ships templates for multiple targets. Adopting a new platform doesn't mean rebuilding your modeling foundation.
What ships today
- Snowflake samples — Data Vault Virtual Data Warehouse, Persistent Staging Area. See the reference.
- SQL Server samples — Data Vault Virtual + Physical Data Warehouse, Persistent Staging Area, plus the DIRECT framework and Testing framework references.
- Microsoft Fabric sample (preview) — Persistent Staging Area adapted for PySpark notebooks.
- 20+ production templates covering staging, integration, Data Vault, and documentation patterns across the platforms above. Browse the template library.
- Anywhere else templates can target — Handlebars produces any text. PostgreSQL DDL, Databricks SQL, BigQuery — if you have a target and a syntax, you have a template.