Pgvector compatibility

Pgvecto.rs is natively compatible with pgvector at:

• Create table like CREATE TABLE t (val vector(3))
• Query vectors like INSERT INTO t (val) VALUES ('[0.6,0.6,0.6]')

Pgvecto.rs can be configured to be compatible with pgvector at:

• Create vector indexes like CREATE INDEX ON t USING hnsw (val vector_ip_ops);
• Query options like SET ivfflat.probes=10;

This feature is called compatibility mode. It can be enabled with SET vectors.pgvector_compatibility=on.

Options & Variables

For index ivfflat and hnsw only the following options and variables are available.

• Default value for options is different from pgvecto.rs original, which keeps the same as in pgvector.
• Default value for variables is the same as in pgvecto.rs.

Options for ivfflat:

Key	Type	Default	Description
lists	integer	100	Number of cluster units.

Variables for ivfflat:

Option	Type	Default	Description
ivfflat.probes	integer ([1, 1000000])	10	Number of lists to scan.

WARNING

Default value of ivfflat.probes is 10 instead of 1 from pgvector.

Options for hnsw:

key	type	default	description
m	integer	16	Maximum degree of the node.
ef_construction	integer	64	Search extent in construction.

Variables for hnsw:

Option	Type	Default	Description
hnsw.ef_search	integer ([1, 65535])	100	Search scope of HNSW.

WARNING

Default value for hnsw.ef_search is 100 instead of 40 from pgvector.

TIP

The original syntax of pgvecto.rs is still available even in compatibility mode.

You can use it with the vectors index like before:

SET vectors.ivf_nprobe=20;
CREATE INDEX ON items USING vectors (embedding vector_l2_ops)
WITH (options = $$
[indexing.ivf]
quantization.product.ratio = "x16"
$$);

Examples

It's easy to enable compatibility mode and start a vector query.

DROP TABLE IF EXISTS t;
SET vectors.pgvector_compatibility=on;
SET hnsw.ef_search=40;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) SELECT ARRAY[random(), random(), random()]::real[] FROM generate_series(1, 1000);
CREATE INDEX hnsw_l2_index ON t USING hnsw (val vector_cosine_ops);
SELECT COUNT(1) FROM (SELECT 1 FROM t ORDER BY val <-> '[0.5,0.5,0.5]' limit 100) t2;
DROP INDEX hnsw_l2_index;

Multiply types of indexes are accepted:

SET vectors.pgvector_compatibility=on;
-- [hnsw + vector_l2_ops] index with default options
CREATE INDEX hnsw_l2_index ON t USING hnsw (val vector_l2_ops);
-- [hnsw + vector_cosine_ops] index with single ef_construction option
CREATE INDEX hnsw_cosine_index ON t USING hnsw (val vector_cosine_ops) WITH (ef_construction = 80);
-- anonymous [hnsw + vector_ip_ops] with all options
CREATE INDEX ON t USING hnsw (val vector_ip_ops) WITH (ef_construction = 80, m = 12);
-- [ivfflat + vector_l2_ops] index with default options
CREATE INDEX ivfflat_l2_index ON t USING ivfflat (val vector_l2_ops);
-- [ivfflat + vector_ip_ops] index with all options
CREATE INDEX ivfflat_ip_index ON t USING ivfflat (val vector_cosine_ops) WITH (nlist = 80);
-- anonymous [ivf + vector_ip_ops] with all options
CREATE INDEX ON t USING ivfflat (val vector_ip_ops) WITH (lists = 80)

Limitation

For compatibility, we strive to maintain a consistent user experience, but there are still some limitations in two aspects:

• Some features of pgvector.rs are not available in `compatibility mode'.
• Some features of pgvector are different in `compatibility mode

Inaccessible features of pgvecto.rs

When executing SQL statements in compatibility mode without vectors index, some features of pgvecto.rs are not accessible:

• flat index
• Quantization, including scalar quantization and product quantization
• Prefilter and vbase

Difference from pgvector

The compatibility mode focuses on the most commonly used features for creating indexes. So far, there are still a few differences from pgvector.

Known problems are not limited to:

• Create btree index on vector type data is not supported
• Create vector indexes is asynchronous at pgvecto.rs, instead of synchronous at pgvector
• Default value of variable is different from pgvector