May 16, 2024 — Vector data type and vector similarity functions — General Availability

With this release, we are pleased to announce the general availability of VECTOR data type, vector similarity functions, and the vector embedding function. These features enable important applications that require semantic vector search and retrieval.

For more information, see Vector Embeddings.

New SQL data type

The following data type is now generally available with this release:

Category

New data type

Description

Vector

VECTOR

With the VECTOR data type, Snowflake encodes and processes vectors efficiently. This data type supports semantic vector search and retrieval applications, such as RAG-based applications, and common operations on vectors in vector-processing applications.

New SQL functions

The following functions are now generally available with this release:

Function Category

New Function

Description

Vector Similarity Function

VECTOR_INNER_PRODUCT

Returns the inner product of two vectors. The inner product (also known as the dot or scalar product) multiplies two vectors

Vector Similarity Function

VECTOR_L2_DISTANCE

Measures the L2 distance between two vectors.

Vector Similarity Function

VECTOR_COSINE_SIMILARITY

Measures the cosine similarity between two vectors, which is the angular distance between the vectors in a multi-dimensional space.

LLM Function

EMBED_TEXT_768 (SNOWFLAKE.CORTEX)

Creates a vector embedding for a given string of text in English.