Vector and Semantic Search in the Lakehouse

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gete6data · 11m ago

Vector and semantic search let lakehouse teams unlock 80% of enterprise data that lives in free-form text, images, and other unstructured formats. By embedding high-dimensional vectors directly into the SQL optimizer, e6data’s “Unify, Don’t Migrate” engine runs cosine-similarity joins faster without extra ETL or a separate vector database. The result: lower costs, simpler pipelines, and far richer insights from customer voice, support chats, docs, and more.

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Vector and Semantic Search in the Lakehouse

Comments (1)