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AI Knowledge is dynamic, infinitely growing. However, server databases cannot scale with infinite AI Knowledge because of their static, monolithic architecture.
Server databases are monolithic always-on servers running 24/7 whether data is accessed or not.
They scale horizontally by just cloning the monolithic system. Sharding mostly requires 2x-3x the number of nodes.
Since starting a large monolithic server node takes minutes and scaling down sharded systems causes computationally intensive data reorganization overhead that can slow down the entire system, most database clusters are also static in practice.
Monolithic systems as well as static clusters are always over-provisioned to handle peak loads, which usually only occur rarely. Up to 80% of their computing power and resulting energy consumption is wasted on idle resources.
Cloud databases are also always-on servers, since starting a new monolithic database server node on-demand takes minutes. To make expensive, always-on databases in the cloud more affordable, providers charge their customers only for usage and call it Serverless - but must pay the full energy bills themselves.