Databricks details improvements to Lakebase Postgres caching
Databricks says they've improved how Lakebase Postgres manages in-memory caching for customer databases. The platform now aims to dynamically adjust the memory it uses for caching based on workload, using up to 75% of available memory, rather than relying on static settings that require a reboot to change. The changes are meant to boost speed and handle workloads more efficiently.
- Lakebase Postgres now adapts memory cache usage automatically
- Dynamic caching uses up to 75% of available memory
- Old method required a reboot to change memory settings
- Improvements target both speed and lower operational hassle
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