Databricks
Data and AI lakehouse platform; the SQL Statement Execution API runs SQL on warehouses, and REST APIs cover jobs and clusters.
- Category
- Cloud & Data Platforms
- Type
- Data warehouse & lakehouse
- Interface
- REST API
- Built with
- Connect Any API
- Credentials
- Access token, OAuth 2.0
02Data
What you can sync.
- Sql query results
- Tables
- Job runs
- Clusters
- Billable usage
Put Databricks sql query results next to revenue and usage, so every cost has an owner and a reason.
Need more? Name any other Databricks data the API returns, and the AI adds it to the connector.
03Credentials
Credentials you will need.
- An access token
- OAuth 2.0 (client ID, client secret, refresh token)
Databricks uses an access token or OAuth 2.0 (client ID, client secret, refresh token). You add the credentials once, when the AI asks for them, and it tells you where to create them in Databricks if you need help.
04How it works
How it works in DataMind.
-
Pick Databricks.
Open Lake, pick Databricks in the source picker and name the connection. Connect Any API opens with a ready prompt that points the AI at the Databricks API docs.
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Answer a few questions.
The AI reads the Databricks documentation, then asks which credentials you will use, which data to sync (for example sql query results and tables), whether you want a one-time load or a recurring sync, and which accounts or filters apply.
-
Your data lands in Lake.
It builds the connector, tests it and shows you sample rows. Then Databricks data loads into your Lake on your schedule, ready for the Warehouse, DataPrism BI and AI Minds.
05Related
