Introducing Always-On pricing: automatic savings for Databricks Lakebase

Summary

Databricks introduces Always-On pricing for Lakebase, offering a lower rate for baseline compute while retaining elastic autoscaling. On any Lakebase Postgres Autoscaling project, operators turn off scale-to-zero and set an autoscaling range; the minimum capacity becomes the baseline, which receives the lower rate after 24 hours of continuous use. Capacity above the minimum continues to autoscale up to the configured maximum and is billed at standard Autoscaling rates, while users can re-enable scale-to-zero later. The pricing targets established workloads with a consistent activity floor; intermittent or new workloads can retain scale-to-zero to avoid paying for idle hours and uncertain baseline estimates. The announcement says the baseline price is 25% lower, and an additional 50% promotional discount runs through January 31, 2027.

Context

Managed operational databases have traditionally required a choice between provisioned capacity, which can be oversized for demand spikes, and serverless capacity, which has a higher per-hour rate. Lakebase positions Always-On pricing for established workloads with a consistent baseline and intermittent peaks, removing the need to choose between predictable lower-cost capacity and elasticity.

Approach / What changed

On a Lakebase Postgres Autoscaling project, turn off scale-to-zero and configure the autoscaling range. The minimum capacity becomes the Always-On baseline and receives the lower rate after 24 hours of continuous use, while capacity above the minimum autoscale to the configured maximum at standard Autoscaling rates. Scale-to-zero can be re-enabled later.

Takeaways

• The Always-On baseline rate is 25% lower after 24 hours of continuous use, with no long-term commitment or required over-provisioning.
• Capacity above the configured minimum continues to autoscale for spikes and is billed at regular Autoscaling rates on the same database.
• Scale-to-zero remains the recommended default for new or intermittent workloads when baseline demand is unknown or the database is frequently idle.

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