Scale your workloads without paying all-RAM prices | Redis

This post introduces Redis Flex, a tiering solution combining RAM and SSD, as a strategy to mitigate rising memory costs impacting in-memory databases, particularly for AI workloads like agents and feature stores. It explains how tiering works by keeping hot data in RAM and less frequently accessed data on SSD, allowing for terabyte-scale datasets with a reduced RAM footprint and significant cost savings (up to 80% less per gigabyte). The post highlights that Flex supports dynamic adjustment of the RAM ratio without code changes and mentions its extension to Redis Search for storing large indexes on SSD (in preview).