Polyglot Storage for Chatbot Memory on Google Cloud
🧠 This article describes a polyglot storage pattern on Google Cloud to preserve conversational continuity for scaled chatbots. It recommends Memorystore for Redis for sub‑millisecond short‑term context, Cloud Bigtable as a petabyte‑scale mid‑term system of record, and BigQuery for long‑term archival and analytics. The design delegates unstructured artifacts to Cloud Storage and uses an async pipeline to balance low latency and durable persistence. Practical configuration and migration pointers help teams implement responsive, analyzable agent memory.
