Databricks: Always-On Pricing
Databricks introduces Always-On pricing for Lakehouse Postgres, offering a 25% discount on baseline capacity without long-term commitments.
Visual TL;DR
serverless flexibility vs. provisioned cost predictability tradeoff
From the article 2 mentionsDatabricks is aiming to simplify cloud database costs with its new Always-On pricing for Databricks Lakebase.
From the article 2 mentionsUsers can activate Always-On pricing by disabling the scale-to-zero feature and defining an autoscaling range for their Lakebase Postgres instance.
From the articleUsers can activate Always-On pricing by disabling the scale-to-zero feature and defining an autoscaling range for their Lakebase Postgres instance.
From the articleOnce the minimum capacity is established as the baseline, it automatically qualifies for the lower Always-On rate after 24 hours of continuous use.
managed Postgres database for Databricks Lakehouse
From the articleThis move follows other enhancements to Databricks Lakehouse, such as native Postgres synchronization, as detailed in Databricks Lakehouse Gets Postgres Boost on Azure.
new pricing model for Databricks Lakehouse Postgres
From the article 7 mentionsThe new Always-On pricing offers a 25% reduction on baseline compute capacity for its managed Postgres database.
offers a 25% reduction on baseline compute capacity
From the article 5 mentionsDatabricks is also offering an additional 50% promotional discount on top of Always-On pricing until January 31, 2027.
From the articleThis aims to eliminate the need for manual optimization or lengthy commitments to achieve cost savings.
without long-term commitments for cost savings
From the articleThis aims to eliminate the need for manual optimization or lengthy commitments to achieve cost savings.
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Written by
Daniel SingerEditor, StartupHub.ai
Daniel Singer is the editor of StartupHub.ai, a technology expert and thought leader on AI and its applications across sectors, from fintech and healthcare to developer tooling and consumer software. He writes and tests the tools covered here thoroughly and regularly, and built StartupHub.ai to give founders, operators and buyers a clearer read on what they are actually being sold.
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