Semantic Search Using CockroachDB

CockroachDB's latest release, version 24.2, introduces support for the VECTOR data type and a set of compatible functions for computing similarity between vectors. This new feature demonstrates CockroachDB's expanding support for AI-driven applications such as Large Language Models (LLMs). The article provides an overview of semantic search using vector support in CockroachDB, which allows users to search for matching documents based on the meaning of the text rather than just word matches. This is achieved through text embeddings that map words, phrases, or sentences into different regions of a vector space with multiple dimensions. The article also discusses K-Means clustering and its role in categorizing a collection of vectors based on similarity to improve search performance. Overall, CockroachDB's support for vectors has the potential to help developers deliver always-on AI-driven experiences.