The Ultimate Guide to High Availability with MariaDB

Vector Overview

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MariaDB starting with 11.7.1

Vectors were introduced in MariaDB 11.7.1

MariaDB Vector is a feature that allows MariaDB Server to perform as a relational vector database. Vectors generated by your favourite AI model can be stored and searched for in MariaDB.

The initial implementation uses the modified HNSW algorithm for searching in the vector index (to solve the so-called Approximate Nearest Neighbor problem), and defaults to Euclidean distance. Concurrent reads/writes and all transaction isolation levels are supported.

MariaDB uses int16 for indexes, which gives 15 bits to store the value, rather than 10 bits for float16.

Creating

Vectors are defined using VECTOR INDEX for the index definition in the CREATE TABLE with vectors statement. 

CREATE TABLE v (
     id INT PRIMARY KEY,
     v VECTOR(5) NOT NULL,
     VECTOR INDEX (v)
);

Inserting

Vector columns store 32-bit IEEE 754 floating point numbers.

INSERT INTO v VALUES 
     (1, x'e360d63ebe554f3fcdbc523f4522193f5236083d'),
     (2, x'f511303f72224a3fdd05fe3eb22a133ffae86a3f'),
     (3,x'f09baa3ea172763f123def3e0c7fe53e288bf33e'),
     (4,x'b97a523f2a193e3eb4f62e3f2d23583e9dd60d3f'),
     (5,x'f7c5df3e984b2b3e65e59d3d7376db3eac63773e'),
     (6,x'de01453ffa486d3f10aa4d3fdd66813c71cb163f'),
     (7,x'76edfc3e4b57243f10f8423fb158713f020bda3e'),
     (8,x'56926c3fdf098d3e2c8c5e3d1ad4953daa9d0b3e'),
     (9,x'7b713f3e5258323f80d1113d673b2b3f66e3583f'),
     (10,x'6ca1d43e9df91b3fe580da3e1c247d3f147cf33e');

Alternatively one can use VEC_FromText() function:

INSERT INTO v VALUES
  (1,Vec_FromText('[0.418708,0.809902,0.823193,0.598179,0.0332549]')),
  (2,Vec_FromText('[0.687774,0.789588,0.496138,0.57487,0.917617]')),
  (3,Vec_FromText('[0.333221,0.962687,0.467263,0.448235,0.475671]')),
  (4,Vec_FromText('[0.822185,0.185643,0.683452,0.211072,0.554056]')),
  (5,Vec_FromText('[0.437057,0.167281,0.0770977,0.428638,0.241591]')),
  (6,Vec_FromText('[0.76956,0.926895,0.803376,0.0157961,0.589042]')),
  (7,Vec_FromText('[0.493999,0.641957,0.761598,0.94276,0.425865]')),
  (8,Vec_FromText('[0.924108,0.275466,0.0543329,0.0731585,0.136344]')),
  (9,Vec_FromText('[0.186956,0.69666,0.0356002,0.668875,0.84722]')),
  (10,Vec_FromText('[0.415294,0.609278,0.426765,0.988832,0.475556]'));

Querying

VEC_DISTANCE_EUCLIDEAN is a function that calculates a Euclidean (L2) distance between two points.

SELECT id FROM v ORDER BY 
  VEC_DISTANCE_EUCLIDEAN(v, x'6ca1d43e9df91b3fe580da3e1c247d3f147cf33e');
+----+
| id |
+----+
| 10 |
|  7 |
|  3 |
|  9 |
|  2 |
|  1 |
|  5 |
|  4 |
|  6 |
|  8 |
+----+

Most commonly, this kind of query is done with a limit, for example to return vectors that are closest to a given vector, such as from a user search query, image or a song fragment.

SELECT id FROM v 
  ORDER BY VEC_DISTANCE_EUCLIDEAN(v, x'6ca1d43e9df91b3fe580da3e1c247d3f147cf33e') LIMIT 2;
+----+
| id |
+----+
| 10 |
|  7 |
+----+

System Variables

There are a number of system variables used for vectors. See Vector System Variables.

See Also

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