What is Vector Search?

Vector search is a retrieval method that converts unstructured data (text, images, audio) into numerical vector representations and finds similar items by comparing vectors in high-dimensional space, enabling semantic search capabilities beyond keyword matching. This technique leverages embedding models to capture meaning and context, making it foundational for modern AI applications like recommendation systems, similarity matching, and retrieval-augmented generation (RAG). Databricks provides tools and infrastructure to implement vector search at scale within data and AI platforms.

Source: Databricks | 2026-06-23