Overview of vector data types

OceanBase provides vector data types to support AI vector search applications. By using vector data types, you can store and query an array of floating-point numbers, such as [0.1, 0.3, -0.9, ...]. Before using vector data, you need to be aware of the following:

• Both dense and sparse vector data are supported, and all data elements must be single-precision floating-point numbers.

• Element values in vector data cannot be NaN (not a number) or Inf (infinity); otherwise, a runtime error will be thrown.\

• You must specify the vector dimension when creating a vector column, for example, VECTOR(3).

• Creating dense/sparse vector indexes is supported. For details, see vector index.

• Vector data in OceanBase is stored in array form.

• Both dense and sparse vectors support hybrid search.

Syntax

A dense vector value can contain any number of floating-point numbers up to 16,000. The syntax is as follows:

-- Dense vector
'[<float>, <float>, ...]'

A sparse vector is based on the MAP data type and contains unordered key-value pairs. The syntax is as follows:

-- Sparse vector
'{<uint:float>, <uint:float>, ...}'

Examples of creating vector columns and indexes are as follows:

-- Create a dense vector column and index
CREATE TABLE t1(
    c1 INT, 
    c2 VECTOR(3), 
    PRIMARY KEY(c1), 
    VECTOR INDEX idx1(c2) WITH (distance=L2, type=hnsw)
    );

-- Create a sparse vector column and index
CREATE TABLE t2 (
    c1 INT, 
    c2 SPARSEVECTOR,
    VECTOR INDEX idx2(c2) WITH (distance=inner_product)
    );

References

• Create vector indexes
• Use SQL functions