Explore IBM Netezza's native vector capabilities — including vector storage, similarity search, and distance operators built for AI, machine learning, and RAG applications.

Details

As AI and generative AI workloads grow in importance, vector search has become a critical capability for modern analytics platforms. IBM Netezza now ships with a native VECTOR data type — no separate vector database required. In this video, you'll see: native vector column support; similarity search across large datasets; built-in distance operators including Cosine, Euclidean (L2), Manhattan (L1), and Inner Product; Retrieval-Augmented Generation (RAG) use cases; semantic search and AI-powered applications; and SQL-based vector analytics integrated with enterprise data.

Key Capabilities: Vector Database · Similarity Search · AI Analytics · Semantic Search · RAG · Machine Learning · Generative AI

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