Rivery helps you ingest, orchestrate, and take action on all of your data. Rivery empowers organizations to support more data sources, larger and more complex datasets, accelerate time to insights, and increase access to data across the entire organization.
You can integrate your Databricks SQL warehouses (formerly Databricks SQL endpoints) with Rivery.
Note
Rivery does not integrate with Azure Databricks clusters.
Connect to Rivery using Partner Connect
To connect to Rivery using Partner Connect, do the following:
As a security best practice, when you authenticate with automated tools, systems, scripts, and apps, Databricks recommends that you use personal access tokens belonging to service principals instead of workspace users. To create tokens for service principals, see Manage tokens for a service principal.
To connect to Rivery manually, follow the steps in this section.
Tip
If the Rivery tile in Partner Connect has a check mark icon inside of it, you can get the connection details for the connected SQL warehouse by clicking the tile and then expanding Connection details. Note however that the Personal access token here is hidden; you must create a replacement personal access token and enter that new token instead when Rivery asks you for it.
If you sign in to your organization’s Rivery account, there might already be a list of existing connection entries with the Databricks logo. These entries might contain connection details for SQL warehouses in workspaces that are separate from yours. If you still want to reuse one of these connections, and you trust the SQL warehouse and have access to it, choose that destination and skip the remaining steps in this section.
Click Create New Connection.
Choose Databricks. Use the Filter Data Sources box to find it if necessary.
Enter a Connection Name and an optional Description.
Enter the Server Hostname, Port, and HTTP Path from the connection details for your SQL warehouse.
Demonstrate understanding of common data engineering tasks to implement and manage data engineering workloads on Microsoft Azure, using a number of Azure services.