Setup
Confirm prerequisites
A Databricks workspace with at least one running SQL Warehouse.
A Databricks personal access token (PAT). To generate one, go to User Settings > Developer > Access tokens in your Databricks workspace and click Generate new token. Copy the token immediately — it cannot be retrieved later.
The connection details for your SQL Warehouse. To find them, open your Databricks workspace, click SQL Warehouses in the sidebar, select your warehouse, and open the Connection details tab.
Grant the required permissions
The Databricks account you connect must have:
- Databricks SQL entitlement — your user account must have the Databricks SQL entitlement enabled in the workspace.
- CAN USE permission on the target SQL Warehouse — this is the minimum access level required to connect and run queries.
- Data access — your account must have SELECT (or higher) privileges on the catalogs, schemas, and tables you want to query.
Add the connection in Duvo
On the Connections page, open Databricks and fill in these fields:
Your Databricks workspace hostname (e.g.,
dbc-abc123.cloud.databricks.com). Found on the Connection details tab of your SQL Warehouse.The SQL Warehouse HTTP path (e.g.,
/sql/1.0/warehouses/abc123). Found on the Connection details tab of your SQL Warehouse.Your Databricks personal access token (starts with
dapi). Generated from User Settings > Developer > Access tokens in your Databricks workspace.Third-party documentation
Third-party documentation
- Generate a personal access token — Step-by-step guide for creating PATs (AWS docs; Azure and GCP have equivalent pages).
- Get connection details for a compute resource — How to find your Server Hostname and HTTP Path (AWS docs; Azure and GCP have equivalent pages).
- SQL warehouse access control — Managing CAN USE and other warehouse permissions.
Capabilities
- Run SQL queries — Execute analytical queries directly against your Databricks SQL Warehouse and retrieve results.
- Explore your data catalog — Browse catalogs, schemas, and tables using discovery queries to understand available datasets.
- Inspect table structures — View column definitions, data types, and metadata for any table in your lakehouse.
- Pull business metrics — Extract KPIs, performance data, and aggregated insights for reports and downstream workflows.
Key Benefits
- Lakehouse access — Query your unified data platform directly from agents without manual SQL sessions.
- Familiar SQL interface — Use standard SQL to retrieve exactly the data you need from structured and semi-structured sources.
- Secure authentication — Connects through personal access tokens with scoped permissions, keeping your data access controlled.
- Large result handling — Streams query results efficiently using Arrow format, supporting datasets with millions of rows.
- Data-driven automation — Make intelligent workflow decisions based on live lakehouse data rather than stale exports.
Works Well With
Google Sheets
Query Databricks for raw data, then push summarized results into a spreadsheet for stakeholder review.
Microsoft Excel
Query Databricks for raw data, then push summarized results into a spreadsheet for stakeholder review.
Slack
Run scheduled analytical queries and deliver key metrics or alerts directly to your team’s communication channels.
Snowflake
Combine data from multiple warehouse platforms in a single agent to build cross-system reports.
Google BigQuery
Combine data from multiple warehouse platforms in a single agent to build cross-system reports.