> ## Documentation Index > Fetch the complete documentation index at: https://docs.maia.ai/llms.txt > Use this file to discover all available pages before exploring further. # dbt Core export const m_runner = "Maia runner"; export const maia = "Maia"; export const ComponentMetadata = ({warehouses, unsupportedWarehouses = [], componentType, connectionInputs, connectionOutputs}) => { const allWarehouses = [...warehouses.map(w => ({ name: w, supported: true })), ...unsupportedWarehouses.map(w => ({ name: w, supported: false }))]; return

Project Availability	{allWarehouses.map((w, i) => {w.name} {w.supported ? '✅' : '❌'} )}
Component Type	{componentType}
Connection Inputs	{connectionInputs}
Connection Outputs	{connectionOutputs}

; }; Run [dbt](https://www.getdbt.com/product/what-is-dbt) commands as part of an orchestration pipeline. When using [dbt environment variables](https://docs.getdbt.com/docs/build/environment-variables) in this component, the variables must have the prefix `DBT_`. For extracting data from dbt Cloud, use the [dbt Cloud](/docs/components/dbt-cloud) Flex connector instead. * Snowflake credentials, including key-pair authentication, are securely passed from the environment to dbt in the background. For more information about how to use key-pair authentication, read [Using Snowflake key-pair authentication](/docs/administration/snowflake-key-pair-authentication). * This component supports the use of pipeline and project variables. For more information, read [Project and pipeline variables](/docs/guides/variables). * This component programmatically generates the `profiles.yml` file and doesn't provide a parameter to specify an external or custom `profiles.yml`. *** ## Video example

</p> *** ## Properties <ResponseField name="Name" type="string" required> A human-readable name for the component. </ResponseField> {/*  */} <ResponseField name="dbt core version" type="drop-down" required> Select the dbt Core version to use. This drop-down shows the current version of dbt Core which is available to your {m_runner}. A warning will be displayed in the pipeline run details if this doesn't match the {m_runner}'s dbt Core version. In the future, Full SaaS {m_runner}s will support multiple versions of dbt Core and will decline to execute the component instead if the selected version isn't supported. </ResponseField> {/*  */} <ResponseField name="dbt project location" type="drop-down" required> Choose how to access your [dbt project](https://docs.getdbt.com/docs/build/projects). If your Git repository uses Multi-Factor Authentication (MFA), ensure you are using a {maia} project that is associated with your Git repository and then select **Current Project** from the options below. * **External Repository:** Select this option if your dbt project is located in an external Git repository that is not connected to your current {maia} project. This is the default setting. This setting uses username and password authentication. * **Current project:** The dbt Core component will look for a dbt project in the associated project repository. This will make available the **dbt Project** property. Select this option if your dbt project is either: * Already located in the Git repository that you have connected to your {maia} project. * Available to import into the current {maia} project. To do this: 1. Clone your dbt project Git repository to your local machine. 2. Compress the dbt project folder (the folder containing `dbt_project.yml`) into a `.zip` file. 3. Click **Add** → **Import** and select the `.zip` file. <Note> A directory is only considered a dbt project if the directory includes a `dbt_project.yml` file. Read more about [dbt\_project.yml](https://docs.getdbt.com/reference/dbt_project.yml). </Note> </ResponseField> {/*  */} <ResponseField name="dbt project" type="drop-down" required> Select the dbt Project to use. The drop-down will list the top-level name of any directories that are classed as dbt projects (defined by including a `dbt_project.yml` file). Only required if **dbt project location** is **Current project**. </ResponseField> {/*  */} <ResponseField name="dbt command" type="string" required> A dbt command to execute. A single instance of the component runs a single dbt command. To learn more about dbt commands, read [dbt Command reference](https://docs.getdbt.com/reference/dbt-commands). The dbt `run` command runs dbt models stored in the Git repository you have synced with. The `run` command will run all models stored in your repository unless you specify a particular model. Specify a model by running `dbt run --{name_of_dbt_model}`. </ResponseField> {/*  */} <ResponseField name="Git URL" type="string" required> URL to the external Git repository to sync to. Only required if **dbt project location** is **External repository**. </ResponseField> {/*  */} <ResponseField name="Git branch" type="string" required> The Git branch to sync with. Only required if **dbt project location** is **External repository**. </ResponseField> {/*  */} <ResponseField name="Git folder path" type="string"> Path to the folder in your repository that contains the dbt project. Leave empty if the dbt project is at the top of the repository. Only required if **dbt project location** is **External repository**. </ResponseField> {/*  */} <ResponseField name="Git username" type="string" required> Your username for the service that hosts your repository, such as GitHub, Azure DevOps, GitLab, or Bitbucket. If your username and your email address are *not* the same value, you must use your username. Only required if **dbt project location** is **External repository**. </ResponseField> {/*  */} <ResponseField name="Git password" type="drop-down" required> Choose the secret definition that represents your credentials for this connector. Only required if **dbt project location** is **External repository**. If you have not already saved your credentials for this connector as a secret definition, click **Add secret** to create a secret definition representing these credentials. Read [Secrets and secret definitions](/docs/guides/secrets-and-secret-definitions) for details about creating a secret definition. To create a new secret: 1. Click **Manage** to open the **Secret definitions** tab of your project in a new browser tab. 2. Click **Add secret definition**. 3. Configure your secret definition using the table as reference if required. | Property | Description | | -------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Secret definition name | A name for the secret definition. Any whitespace added to the start or end of the secret definition name is automatically trimmed. | | Description | An optional, referential description for the project. Max 256 characters. | | Agent | Select the {m_runner} that will be used by the pipelines that use this secret. This is only required if you have a [Hybrid SaaS solution](/docs/guides/runner-overview#matillion-fully-managed-vs-hybrid-cloud). To learn how to create a {m_runner}, read [Create a {m_runner}](/docs/guides/create-a-runner). | | Secret Name | For a Hybrid SaaS solution only, select a named entry created in [AWS Secrets Manager](https://docs.aws.amazon.com/secretsmanager/latest/userguide/intro.html). | | Secret Key | For a Hybrid SaaS solution only, select a named secret key tied to your secret name. | | Use multi-line text input? | For a [Matillion Full SaaS solution](/docs/guides/runner-overview#matillion-fully-managed-vs-hybrid-cloud) only, toggle "Yes" to enable multi-line text input for secret values that require multi-line input. For example, certificates and SSH keys. | | Secret value | For a Matillion Full SaaS solution only, give a secret value in the field provided. | 4. Click **Create Secret**. 5. Return to the Git Password drop-down and select your new secret definition from the drop-down list. </ResponseField> {/*  */} <ResponseField name="Map dbt environment variables" type="column editor"> Specify any dbt environment variables and their values. <Note> Environment variables passed to this component must have the prefix `DBT_`. </Note> </ResponseField> {/*  */} <ResponseField name="Global configuration in profiles.yml" type="column editor"> Append configuration parameters to the `profiles.yml` file. * **Key:** The parameter name. * **Value:** The parameter value. * **Data Type:** String, number, or Boolean. Read dbt's [About profiles.yml](https://docs.getdbt.com/docs/core/connect-data-platform/profiles.yml) to learn more. </ResponseField> {/*  */} <ResponseField name="Profile configuration in profiles.yml" type="column editor"> Assign additional output parameters or override existing parameters of the `profiles.yml` file. {maia} generates the profile.yml file based on the [environment](/docs/guides/environments) you have configured in {maia}—for instance, if your environment is set up for Snowflake, the Snowflake connection is included in the profile.yml file. * **Key:** The parameter name. * **Value:** The parameter value. * **Data Type:** String, number, or Boolean. Cloud data warehouse parameter documentation is available below: * [Snowflake](https://docs.getdbt.com/docs/core/connect-data-platform/snowflake-setup) * [Databricks](https://docs.getdbt.com/docs/core/connect-data-platform/databricks-setup) * [Amazon Redshift](https://docs.getdbt.com/docs/core/connect-data-platform/redshift-setup) * [Google BigQuery](https://docs.getdbt.com/docs/core/connect-data-platform/bigquery-setup) </ResponseField>