Databricks SQL is the warehousing surface of the Databricks platform, running BI and analytical SQL on the vectorized Photon engine against Delta Lake and Iceberg tables governed by Unity Catalog.
Managed on AWS, Azure, and Google Cloud. SQL warehouses run the vectorized Photon engine against Delta and Iceberg tables in your object storage, governed by Unity Catalog. Classic and Pro compute lives in your cloud account; Serverless lives in Databricks' and bundles infrastructure into the DBU rate. Streaming tables ingest from Kafka, Kinesis, and Pub/Sub.
How Databricks SQL answers the questions Data Warehouses turns on.
| How it works | |
| Compute and storage | MPP over object storage: classic and pro compute in your cloud account, serverless in Databricks' |
| Storage format | Open: Delta Lake and managed or foreign Iceberg in your object storage |
| SQL dialect | ANSI SQL (Spark SQL) |
| Streaming ingest | Native: streaming tables from Kafka, Kinesis, Pub/Sub and cloud storage |
| Time travel | Delta time travel: 7 days of data files by default, 30 days of log, configurable |
| Running it | |
| Where it runs | AWS, Azure and Google Cloud |
| Concurrent users | One cluster per 10 concurrent queries, autoscaled; serverless adds intelligent workload management |
| Acceleration | Photon vectorized engine, predictive I/O, disk cache, materialized views, predictive optimization |
| Access | |
| Access control | Unity Catalog: GRANT on a three-level namespace, row filters and column masks, tag-based ABAC, lineage and audit |
| Cost | |
| Billing unit | DBU-second per warehouse; classic and pro add the cloud VM bill, serverless bundles it |
vs Databricks SQL: Subscription
vs Databricks SQL: Open source (permissive) · Self-hosted · Free · Operational complexity: High · C
vs Databricks SQL: Operational complexity: Low