dbt

dbt (data build tool) enables data teams to transform data using analytics engineering best practices. Use the Altertable adapter to run your dbt models directly in your Altertable lakehouse.

Installation

The Altertable adapter for dbt is available on PyPI and works with dbt-core.

pip install dbt-altertable

Configuration

Add an Altertable profile to your profiles.yml file. By default, dbt looks for profiles in ~/.dbt/profiles.yml, but you can also place it in your project directory or specify a custom location using the --profiles-dir flag. Learn more about dbt profiles in the dbt documentation.

Profile Example

your_project_name:
  target: dev
  outputs:
    dev:
      type: altertable
      username: your_altertable_username
      password: your_altertable_password
      database: your_catalog_name
      schema: your_schema_name

Configuration Parameters

• type: Must be set to altertable (required)
• username: Your Altertable username (required) — find this in the Credentials section of the dashboard
• password: Your Altertable password (required) — find this in the Credentials section of the dashboard
• database: The name of your Altertable connection's catalog where models will be materialized (required)
• schema: The schema within your catalog where models will be created (required)

Usage

Once configured, you can use dbt with Altertable just like any other adapter:

# Test your connection
dbt debug

# Run your models
dbt run

# Test your models
dbt test

# Generate and serve documentation
dbt docs generate
dbt docs serve

Learn more about dbt commands in the dbt documentation.

SQL Dialect

Altertable uses DuckDB as its query engine, so all SQL queries in your dbt models must use DuckDB-flavored SQL. This includes using DuckDB's functions, syntax, and data types.

Learn more about DuckDB SQL in the DuckDB documentation.

Source Code

The adapter source code is available at github.com/altertable-ai/dbt-altertable