🧱Databricks SQL Warehouse

iDBQuery's Databricks connector turns a Databricks SQL Warehouse into a conversational analytics surface across your lakehouse. Provide your workspace host (e.g. `dbc-abcd1234-xy56.cloud.databricks.com`), the HTTP path of a SQL Warehouse from its connection details panel, and a personal access token (or service-principal token), and the schema across catalogs, schemas, and tables visible to that token is introspected immediately. The AI sees Unity Catalog metadata — catalogs, schemas, tables, views, materialized views, columns, data types, partition columns, and the table format (Delta, Iceberg, Parquet) — and uses that to write standard ANSI SQL the warehouse can execute. Every chat question becomes a safe parametrized SELECT, returned as a chart, table, stat card, or dashboard. Databricks-specific features — `LATERAL VIEW EXPLODE` for complex types, `QUALIFY`, window functions, `MERGE`-style read patterns, time-travel queries (`VERSION AS OF` / `TIMESTAMP AS OF`) on Delta tables, geospatial functions — are all in the model's vocabulary. Use a small SQL Warehouse with auto-stop at 10 minutes for analytical workloads to keep DBU consumption predictable. The personal access token is encrypted at rest with strong symmetric encryption, used only at query time, and never returned by any API. The free tier — 1M tokens per month, three sources, five reports, no credit card — lets you validate the workflow before committing. iDBQuery makes the lakehouse a chat window for your team.

• Databricks SQL Warehouse on AWS, Azure, and GCP
• Unity Catalog awareness — catalogs, schemas, tables, views
• Delta, Iceberg, and Parquet tables
• Personal access tokens or service-principal tokens
• Time-travel queries (`VERSION AS OF` / `TIMESTAMP AS OF`)
• Complex types (STRUCT/ARRAY/MAP) via `LATERAL VIEW EXPLODE`
• Read-only enforcement at the connector layer
• Cross-source joins with spreadsheets or other databases