Many organizations continue running short-lived or low-intensity SQL workloads — such as dashboards, exploratory queries, and BI tool integrations — on traditional clusters. This leads to idle compute, overprovisioning, and high baseline costs, especially when the clusters are always-on. Databricks SQL Serverless is optimized for bursty, interactive use cases with auto-scaling and pay-per-second pricing, making it better suited for this class of workloads. Failing to migrate to serverless for these patterns results in unnecessary cost without performance benefit.
Serverless SQL compute is billed per second of execution time based on the size of the virtual warehouse used. Unlike full clusters, serverless compute does not incur idle time charges and automatically scales based on demand. Continuing to use traditional job or all-purpose clusters for low-throughput SQL workloads results in persistent infrastructure costs that serverless options are purpose-built to eliminate.
