Databricks Lakebase Postgres 成本优化指南：按实际工作集配置
Databricks 这份 Lakebase Postgres 省钱指南很实在：2500 GB 库只要 20 GB 热数据就别买 2500 GB 内存，四种配置思路直接抄作业。
Databricks 发布 Lakebase Postgres 成本优化指南，核心原则是 2500 GB 的数据库若热工作集只有 20 GB，就不需要 2500 GB 的内存。指南建议只同步应用实际查询的工作集，并按新鲜度需求选择 Snapshot、Triggered 或 Continuous 三种同步模式。计算资源配置以热数据能放进缓存为准，PITR 和快照则按实际恢复需求设定。完整指南还讲解了如何在保持性能与可用性的同时让成本可预测。
A 2,500 GB database with a 20 GB hot working set doesn’t need 2,500 GB of RAM.
That principle runs through Lakebase Postgres cost optimization: size around what your application actually needs.
✦ Sync only the working set your app queries ✦ Match Snapshot, Triggered or Continuous sync to freshness requirements ✦ Size compute so hot data fits in cache ✦ Set PITR and snapshots around actual recovery needs
The full guide breaks down how to keep costs predictable while maintaining the performance, availability and developer experience applications need: https://t.co/fqn6kftNtc
