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IBM demonstrates extreme scale with a 100B vector database
IBM Research demonstrated the capability to store and search across a database of 100 billion vectors, showcasing extreme-scale vector storage for AI applications. This work addresses the growing need
IBM Research demonstrated the capability to store and search across a database of 100 billion vectors, showcasing extreme-scale vector storage for AI applications. This work addresses the growing need for large-scale similarity search in enterprise AI systems, particularly for retrieval-augmented generation (RAG) and other AI workloads that rely on vector embeddings. The research highlights IBM's advancements in efficient indexing, storage architecture, and query performance at a scale far beyond typical production deployments.
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Source: IBM Research | 2026-04-13