Vector Index

Vector indexes in Databend enable efficient similarity search on high-dimensional vector data using the HNSW (Hierarchical Navigable Small World) algorithm. They support use cases like semantic search, recommendation systems, and AI applications.

Key Feature: Automatic Index Generation

Vector indexes are automatically built as data is written. When you insert or load data into a table with a Vector index, the index is generated automatically without manual intervention. You only need to run REFRESH VECTOR INDEX if you create an index on a table that already contains data.

Vector Index Management

Command	Description
CREATE VECTOR INDEX	Creates a new Vector index for efficient similarity search
REFRESH VECTOR INDEX	Builds index for data that existed before index creation
DROP VECTOR INDEX	Removes a Vector index