Redshift Semantic Layer with Bonnard

Bonnard gives you a Redshift semantic layer defined in YAML, version-controlled, and queryable from AI agents, React components, and REST APIs. Redshift handles large-scale analytics with columnar storage and massively parallel processing. Bonnard connects directly and exposes governed metrics through MCP, React SDK, REST API, and markdown dashboards.

How does Bonnard connect to Redshift?

Add Redshift as a datasource in your Bonnard project. Define the connection in your datasources.yml:

# datasources.yml
datasources:
  - name: redshift_warehouse
    type: redshift
    host: your-cluster.abc123.us-east-1.redshift.amazonaws.com
    port: 5439
    database: analytics
    username: bonnard_readonly
    password: ${REDSHIFT_PASSWORD}
    schema: public
    ssl: true

Then run:

bon datasource add redshift_warehouse
bon deploy

Bonnard connects to your Redshift cluster, introspects your schema, and deploys your semantic layer. Works with both Redshift provisioned clusters and Redshift Serverless. Your warehouse data is queryable through every Bonnard surface within minutes.

What do you get?

Once connected, your Redshift data is available through four surfaces:

MCP server. Run bon mcp and your AI agents (Claude, ChatGPT, Cursor) query governed Redshift metrics with row-level security. Generate publishable keys per tenant for customer-facing agentic analytics.

React SDK. Drop BarChart, LineChart, and BigValue components into your product. Every chart queries your Redshift cluster through the semantic layer with multi-tenant access controls applied automatically.

REST API. Query metrics programmatically from any language or platform. Type-safe queries with the TypeScript SDK or raw HTTP from anywhere.

Markdown dashboards. Author dashboards in markdown, deploy with bon deploy, and share governed views with your team or customers.

How does Bonnard compare to native Redshift analytics?

Capability	Redshift native	Bonnard + Redshift
Metric definitions	SQL views, saved queries	YAML semantic layer (version-controlled)
AI agent access	None	MCP server with publishable keys
Embedded analytics	QuickSight (separate service)	React SDK with multi-tenant auth
Dashboards	QuickSight	Markdown dashboards, deployed via CLI
Multi-tenancy	Schema isolation / row-level security	Publishable keys + automatic row filters
Pre-aggregation	Materialized views (manual)	Automatic pre-aggregation cache
dbt integration	dbt-redshift adapter	bon datasource add --from-dbt imports models
Access control	IAM + Redshift users	YAML-defined RBAC + audit logging
Deployment	SQL scripts	bon deploy (no restart, no SSH)

FAQ

Does Bonnard support Amazon Redshift?

Yes. Redshift is a first-class Bonnard datasource. Both provisioned clusters and Redshift Serverless are supported. Configure your cluster endpoint, credentials, and schema, then deploy.

Does Bonnard work with Redshift Serverless?

Yes. Use your Redshift Serverless endpoint as the host in datasources.yml. Bonnard connects the same way it connects to provisioned clusters. No additional configuration needed.

Can I use pre-aggregations with Redshift?

Yes. The pre-aggregation cache handles this automatically. Define rollups in your cube YAML files and Bonnard builds and refreshes them on schedule. This reduces Redshift compute costs and speeds up repeated queries without manual materialized view management.

Can I import dbt models from Redshift?

Yes. Run bon datasource add --from-dbt pointed at your dbt project using the dbt-redshift adapter. Bonnard imports your models as cubes and your metrics as measures. Layer the semantic layer on top of your existing dbt transformations.