IBM Demonstrates Extreme Scale With A 100B Vector Database
IBM, Monday, April 13th, 2026
The storage-centric vector database fits on a single server to help scale retrieval-augmented generation, unlocking new value from enterprise data.
Content-aware storage (CAS) represents a new value-add paradigm for traditional storage systems. CAS, which aligns storage solutions to meet the needs of new AI workloads, is centered around a pushdown of data processing functions. Specifically, CAS handles document vectorization using LLM-based embedding models - a process normally performed outside of the storage system - to support the retrieval augmented generation (RAG) pipeline.