Supported Platforms
Overview
This extension is designed to work seamlessly with all database adapters that are natively supported by dbt. By leveraging dbt’s robust adapter ecosystem, users can connect to a wide variety of data warehouses and processing engines without additional configuration or compatibility concerns.
Supported Database Adapters
The extension supports, but is not limited to, the following platforms:
- Databricks: Fully compatible with Databricks SQL and Databricks Lakehouse, enabling scalable analytics and data engineering workflows.
- Snowflake: Native support for Snowflake’s cloud data platform, including advanced features such as zero-copy cloning and time travel.
- BigQuery: Integrates with Google BigQuery for fast, serverless analytics over large datasets.
- Redshift: Supports Amazon Redshift, allowing for high-performance data warehousing in the AWS ecosystem.
- Postgres: Works with PostgreSQL databases, both on-premises and in the cloud.
- SQL Server: Compatible with Microsoft SQL Server, supporting enterprise-grade data solutions.
- Spark: Enables analytics and transformations on Apache Spark clusters.
- Other Adapters: The extension is compatible with any adapter officially supported by dbt, including Presto, Trino, and more.
For the most current and comprehensive list of supported adapters, please refer to the official dbt documentation.
GitHub + Model Context Protocol (MCP) Integration
In addition to database adapters, the extension supports integration with both GitHub and Model Context Protocol (MCP). These features allow you to:
- Connect to GitHub-hosted dbt environments: Seamlessly manage and execute dbt projects directly from GitHub repositories.
- Leverage GitHub Actions: Automate dbt runs, testing, and deployments using GitHub Actions workflows.
- Incorporate Model Context Protocol (MCP): Enrich your workflows with dynamic model metadata, including lineage, freshness, and dependency context.