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This guide shows you how to connect your dbt Core project to Coalesce Quality to track model runs, test results, and metadata changes.Prerequisites:
  • Admin access to your Coalesce Quality workspace
  • Ability to modify your dbt orchestration tool (Airflow, GitHub Actions, etc.)
⏱️ Estimated time: 15 minutes
Using dbt Cloud? You can integrate directly through Settings → Integrations → Add Integration → dbt Cloud instead of following this guide.

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Set up dbt Core integration

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Create integration in Coalesce Quality

  1. Navigate to Settings → Integrations → Add Integration
  2. Select dbt Core from the integration options

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Configure integration settings

Integration name: Enter a descriptive name (e.g., Production dbt Core) Generate token: Click Create to generate your integration token. You’ll use this token with the synq-dbt tool to send artifacts securely to Coalesce Quality. Git integration: Select your Git provider to link model changes to repository commits. This enables change tracking and lineage visualization. Relative path to dbt: If your dbt project isn’t in the repository root, specify the directory path (e.g., analytics/dbt/).

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Manage integration tokens

Access token management through Settings → Integrations, then select your dbt Core integration and click Manage tokens.
dbt Core token management interface
From the token management screen, you can:
  • Create new tokens for different environments
  • Invalidate compromised tokens
  • Copy token snippets for easy integration
List of dbt Core integration tokens

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Install synq-dbt

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About synq-dbt

synq-dbt is a command-line wrapper that runs your existing dbt Core commands and automatically uploads artifacts to Coalesce Quality. It’s version-agnostic — working with any dbt Core version by passing all arguments directly to your installed dbt — and integrates seamlessly with orchestration tools like Airflow, GitHub Actions, and Dagster. Collected artifacts:
  • manifest.json — Project structure and dependencies
  • run_results.json — Execution status and performance metrics
  • catalog.json — Complete data warehouse schema information
  • sources.json — Source freshness test results
How it works:
  1. Executes your locally installed dbt Core with all provided arguments (version-agnostic, passes arguments directly)
  2. Captures the original dbt exit code
  3. Reads your SYNQ_TOKEN environment variable
  4. Uploads artifacts from the target directory to Coalesce Quality
  5. Returns the original dbt Core exit code, even if upload fails (preserving pipeline behavior and ensuring CI/CD reliability)

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Installation methods

Choose the installation method that matches your dbt orchestration setup:

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Airflow with DockerOperator

  1. Set environment variable: In Airflow UI, create a new environment variable SYNQ_TOKEN with your integration token.
  2. Update Dockerfile: 
ENV SYNQ_VERSION=v2.0.0
RUN wget -O /usr/bin/synq-dbt https://github.com/getsynq/synq-dbt/releases/download/${SYNQ_VERSION}/synq-dbt-amd64-linux && \
    chmod +x /usr/bin/synq-dbt
  1. Update your operator:
KubernetesPodOperator(
    env_vars={
        "SYNQ_TOKEN": Variable.get("SYNQ_TOKEN"),
        # For US region: "SYNQ_API_ENDPOINT": "https://api.us.synq.io"
    },
    cmds=["synq-dbt"],
    arguments=["build"],  # Your dbt command here
    # ... other configuration
)
Linking dbt models to Airflow tasks: To automatically link your dbt models with the Airflow tasks that execute them, see the Airflow + dbt Core Linking guide. This enables bidirectional visibility between your orchestration and data layers.

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Airflow with dbt Plugin

  1. Set environment variable: Create SYNQ_TOKEN in Airflow UI.
  2. Install synq-dbt: 
export SYNQ_VERSION=v2.0.0
wget -O ./synq-dbt https://github.com/getsynq/synq-dbt/releases/download/${SYNQ_VERSION}/synq-dbt-amd64-linux
chmod +x ./synq-dbt && mv synq-dbt /usr/local/bin/synq-dbt
  1. Update DbtOperator:
dbt_run = DbtRunOperator(
    dbt_bin='synq-dbt',
    env={
        "SYNQ_TOKEN": Variable.get("SYNQ_TOKEN"),
        # For US region: "SYNQ_API_ENDPOINT": "https://api.us.synq.io"
    },
    # ... other configuration
)
For linking dbt models to Airflow tasks, see the Airflow + dbt Core Linking guide.

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Dagster

  1. Configure environment: Add SYNQ_TOKEN=<your-token> to your .env file. For US region workspaces, also add SYNQ_API_ENDPOINT=https://api.us.synq.io.
  2. Update resources in definitions.py: 
resources = {
    "dbt": DbtCliResource(
        dbt_executable='synq-dbt', 
        project_dir=os.fspath(dbt_project_dir)
    ),
}
  1. Update assets in assets.py:
@dbt_assets(manifest=dbt_manifest_path)
def jaffle_shop_dbt_assets(context: AssetExecutionContext, dbt: DbtCliResource):
    dbt_target_path = Path('target')
    yield from dbt.cli(["build"], target_path=dbt_target_path, context=context).stream()

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Docker

Add to your Dockerfile: 
ENV SYNQ_VERSION=v2.0.0
RUN wget -O /usr/bin/synq-dbt https://github.com/getsynq/synq-dbt/releases/download/${SYNQ_VERSION}/synq-dbt-amd64-linux && \
    chmod +x /usr/bin/synq-dbt

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Linux/macOS

Download and install: 
# For Linux
export SYNQ_VERSION=v2.0.0
wget -O ./synq-dbt https://github.com/getsynq/synq-dbt/releases/download/${SYNQ_VERSION}/synq-dbt-amd64-linux

# For macOS
wget -O ./synq-dbt https://github.com/getsynq/synq-dbt/releases/download/${SYNQ_VERSION}/synq-dbt-arm64-darwin

# Make executable and move to PATH
chmod +x ./synq-dbt && mv synq-dbt /usr/local/bin/synq-dbt

# Set your token and test
export SYNQ_TOKEN=<your-token>
synq-dbt --version

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Use synq-dbt

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Basic usage

Replace your existing dbt Core commands with synq-dbt: 
# Instead of: dbt run --select finance --threads 5
synq-dbt run --select finance --threads 5

# Instead of: dbt test --select reports  
synq-dbt test --select reports

# Instead of: dbt build
synq-dbt build
All dbt Core arguments and options work exactly the same way.

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Upload existing artifacts

If you have already generated dbt artifacts and want to upload them to Coalesce Quality: 
export SYNQ_TOKEN=<your-token>
synq-dbt synq_upload_artifacts
Include dbt logs: 
dbt build | tee dbt.log
synq-dbt synq_upload_artifacts --dbt-log-file dbt.log

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Configuration options

Environment variables:
  • SYNQ_TOKEN — Your integration token (required)
  • SYNQ_TARGET_DIR — Artifact directory path (default: target/)
  • SYNQ_API_ENDPOINT — API endpoint for your region (required for US region)
Regional configuration:
EU region customers (default) don’t need to set SYNQ_API_ENDPOINT. US region customers must configure it.
For US region workspaces, set the API endpoint: 
export SYNQ_API_ENDPOINT=https://api.us.synq.io
For EU region workspaces (default), no additional configuration needed — the tool automatically uses https://developer.synq.io. Network requirements:
  • Allow outbound HTTPS traffic to developer.synq.io:443 (EU region) or api.us.synq.io:443 (US region)
Data visibility:
  • Artifacts appear in Coalesce Quality within minutes of upload under normal conditions
  • Failed uploads are logged and can be retried
  • Typical payload sizes range from several megabytes to tens of megabytes depending on project size
For advanced configuration options and troubleshooting, see the synq-dbt GitHub repository.