SQL warehouse types
Databricks SQL supports the following SQL warehouse types:
Serverless
Pro
Classic
Each SQL warehouse type has different performance capabilities. The following table shows the performance features supported by each SQL warehouse type.
Warehouse type |
Photon Engine |
Predictive IO |
Intelligent Workload Management |
---|---|---|---|
Serverless |
X |
X |
X |
Pro |
X |
X |
|
Classic |
X |
The following list describes each performance feature:
Photon: The native vectorized query engine on Databricks. It makes your existing SQL and DataFrame API calls faster and reduces your total cost per workload.
Predictive IO: A suite of features for speeding up selective scan operations in SQL queries. Predictive IO can provide a wide range of speedups.
Intelligent workload management (IWM): A set of features that enhances Databricks SQL Serverless’s ability to process large numbers of queries quickly and cost-effectively. Using AI-powered prediction and dynamic management techniques, IWM works to ensure that workloads have the right amount of resources quickly. The key difference lies in the AI capabilities in Databricks SQL to respond dynamically to workload demands rather than using static thresholds.
Note
For pricing for each warehouse type and a detailed feature comparison, see Databricks SQL. To learn about the latest Databricks SQL features, see Databricks SQL release notes.
Performance differences between SQL warehouse types
Each SQL warehouse type has different performance characteristics.
Serverless SQL warehouses
Using the Databricks serverless architecture, a serverless SQL warehouse supports all of the performance features of Databricks SQL. With a serverless SQL warehouse and its performance features, you get:
Rapid startup time (typically between 2 and 6 seconds).
Rapid upscaling to acquire more compute when needed for maintaining low latency.
Query admittance closer to the hardware’s limitation rather than the virtual machine.
Quick downscaling to minimize costs when demand is low, providing consistent performance with optimized costs and resources.
For best startup performance, most efficient IO, smarter handling of query demand that varies greatly over time, and rapid autoscaling when query queuing occurs, choose a serverless SQL warehouse. See Serverless autoscaling and query queuing.
A serverless SQL warehouse performs well with these types of workloads:
ETL
Business intelligence
Exploratory analysis
Important
SQL warehouses do not support credential passthrough. Databricks recommends using Unity Catalog for data governance. See What is Unity Catalog?.
Pro SQL warehouses
A pro SQL warehouse supports Photon and Predictive IO, but does not support Intelligent Workload Management. With a pro SQL warehouse (unlike a serverless SQL warehouse), the compute layer exists in your your AWS account account rather than in your Databricks account. As a result, a pro SQL warehouse does not support Intelligent Workload Management, making it less responsive to query demand that varies greatly over time and unable to autoscale as rapidly as a serverless SQL warehouse. A pro SQL warehouse takes several minutes to start up (typically approximately 4 minutes) and scales up and down with less responsiveness than a serverless SQL warehouse. See Queueing and autoscaling for pro and classic SQL warehouses.
Use a pro SQL warehouse when:
Serverless SQL warehouses are not available in a region.
You have custom-defined networking and want to connect to databases in your network in the cloud or on-premises for federation or a hybrid-type architecture. For example, use a pro SQL warehouse if you want to put other services into your network such as an event bus or databases, or you want to connect your network to your on-premises network.
Classic SQL warehouses
A classic SQL warehouse supports Photon, but does not support Predictive IO or Intelligent Workload Management. With a classic SQL warehouse (unlike a serverless SQL warehouse), the compute layer exists in your AWS account account rather than in your Databricks account. Without support for Predictive IO or Intelligent Workload Management, a classic SQL warehouse provides only entry level performance and less performance than either a serverless or a pro SQL warehouse. A classic SQL warehouse also takes several minutes to start up (typically approximately 4 minutes) and scales up and down with less responsiveness than a serverless SQL warehouse. See Queueing and autoscaling for pro and classic SQL warehouses.
Use a classic SQL warehouse to run interactive queries for data exploration with entry-level performance and Databricks SQL features.
Note
For information about sizing your SQL warehouse and how your SQL warehouse scales in response to query queuing, see Queueing and autoscaling for pro and classic SQL warehouses.
What are the warehouse type defaults?
For workspaces in regions that support serverless SQL warehouses and satisfy the requirements:
Using the UI, the default SQL warehouse type is serverless.
If your account needs updated terms of use, workspace admins are prompted in the Databricks SQL UI.
Using the SQL warehouses API with default parameters, the default SQL warehouse type is classic. To use serverless, set the
enable_serverless_compute
parameter totrue
and also setwarehouse_type
topro
. If this workspace used the SQL warehouses API to create a warehouse between September 1, 2022 and April 30, 2023, and fits the requirements for serverless SQL warehouses, the default remains set totrue
. To avoid ambiguity, especially for organizations with many workspaces, Databricks recommends that you always set this field.If the workspace uses a legacy external Hive metastore, serverless SQL warehouses are not supported. The default SQL warehouse type is the same as if serverless compute were disabled, which is pro in the UI and classic using the API. Also, contact your Databricks account team to learn more about Unity Catalog or other options.
For workspaces that do not support serverless SQL warehouses:
Using the UI, the default SQL warehouse type is pro.
Using the SQL warehouses API with default parameters, the default SQL warehouse type is classic.
Note
If your account needs updated terms of use, workspace admins are prompted in the Databricks SQL UI.