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Databricks SQL is a cloud data warehouse built on lakehouse architecture. It runs directly on your data lake, supports ANSI SQL with Delta Lake extensions, and provides the tools to build highly performant, cost-effective data warehouses without moving your data.
Interfaces and tools
Databricks SQL runs on SQL warehouses and is accessible from multiple interfaces for querying, visualization, pipeline management, and automation.
| Interface | Description |
|---|---|
| SQL editor | Write and run SQL queries with integrated AI assistance, code comments, and version history. |
| Notebooks | Run SQL alongside Python, Scala, or R by attaching a notebook to a SQL warehouse. |
| AI/BI | Create AI-powered dashboards and Genie spaces for self-service data analysis and conversational data exploration. |
| Metric views | Define reusable business metrics with consistent calculations using a semantic layer. |
| Alerts | Monitor query results, evaluate conditions, and deliver notifications automatically. |
| Jobs | Schedule SQL queries for automated data processing and reporting workflows. |
| ETL | Define and refresh streaming tables and materialized views directly in Databricks SQL for incremental ETL pipelines. |
| REST API | Automate and manage Databricks SQL objects programmatically. |
Monitor and optimize
| Resource | Description |
|---|---|
| Query history | Review past query runs, execution times, and resource usage across your warehouse. |
| Query profile | Inspect the execution plan for a query to identify bottlenecks and optimization opportunities. |
| Query performance insights | Get automatic insights and recommendations when queries run inefficiently. |
Get started
If you're new to Databricks SQL, start with the concepts and then follow a hands-on walkthrough.
| Resource | Description |
|---|---|
| Databricks SQL concepts | Learn core concepts including queries, SQL warehouses, dashboards, and data management. |
| Data warehousing architecture | Understand lakehouse architecture, medallion layers, and data modeling approaches for Databricks SQL. |
| Get started with data warehousing | Follow a complete walkthrough covering sample dashboards, notebooks, jobs, data ingestion, and SQL warehouse setup. |
| Unity Catalog metric views | Define consistent, reusable business metrics with a semantic layer for use across queries and dashboards. |
| Create an AI/BI dashboard | Build and publish your first dashboard with datasets, visualizations, and filters using AI-assisted authoring. |