fix(deps): update database tools (minor)

[renovate]

This PR contains the following updates:

Package	Change	Age	Adoption	Passing	Confidence
drizzle-kit (source)	0.30.6 -> 0.31.0
drizzle-orm (source)	0.41.0 -> 0.42.0

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Release Notes

drizzle-team/drizzle-orm (drizzle-kit)

v0.31.0

Compare Source

Breaking changes

Note: [email protected] can be used with [email protected] or higher. The same applies to Drizzle Kit. If you run a Drizzle Kit command, it will check and prompt you for an upgrade (if needed). You can check for Drizzle Kit updates. below

PostgreSQL indexes API was changed

The previous Drizzle+PostgreSQL indexes API was incorrect and was not aligned with the PostgreSQL documentation. The good thing is that it was not used in queries, and drizzle-kit didn't support all properties for indexes. This means we can now change the API to the correct one and provide full support for it in drizzle-kit

Previous API

• No way to define SQL expressions inside .on.
• .using and .on in our case are the same thing, so the API is incorrect here.
• .asc(), .desc(), .nullsFirst(), and .nullsLast() should be specified for each column or expression on indexes, but not on an index itself.

// Index declaration reference
index('name')
  .on(table.column1, table.column2, ...) or .onOnly(table.column1, table.column2, ...)
  .concurrently()
  .using(sql``) // sql expression
  .asc() or .desc()
  .nullsFirst() or .nullsLast()
  .where(sql``) // sql expression

Current API

// First example, with `.on()`
index('name')
  .on(table.column1.asc(), table.column2.nullsFirst(), ...) or .onOnly(table.column1.desc().nullsLast(), table.column2, ...)
  .concurrently()
  .where(sql``)
  .with({ fillfactor: '70' })

// Second Example, with `.using()`
index('name')
  .using('btree', table.column1.asc(), sql`lower(${table.column2})`, table.column1.op('text_ops'))
  .where(sql``) // sql expression
  .with({ fillfactor: '70' })

New Features

🎉 "pg_vector" extension support

There is no specific code to create an extension inside the Drizzle schema. We assume that if you are using vector types, indexes, and queries, you have a PostgreSQL database with the pg_vector extension installed.

You can now specify indexes for pg_vector and utilize pg_vector functions for querying, ordering, etc.

Let's take a few examples of pg_vector indexes from the pg_vector docs and translate them to Drizzle

L2 distance, Inner product and Cosine distance

// CREATE INDEX ON items USING hnsw (embedding vector_l2_ops);
// CREATE INDEX ON items USING hnsw (embedding vector_ip_ops);
// CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops);

const table = pgTable('items', {
    embedding: vector('embedding', { dimensions: 3 })
}, (table) => ({
    l2: index('l2_index').using('hnsw', table.embedding.op('vector_l2_ops'))
    ip: index('ip_index').using('hnsw', table.embedding.op('vector_ip_ops'))
    cosine: index('cosine_index').using('hnsw', table.embedding.op('vector_cosine_ops'))
}))

L1 distance, Hamming distance and Jaccard distance - added in pg_vector 0.7.0 version

// CREATE INDEX ON items USING hnsw (embedding vector_l1_ops);
// CREATE INDEX ON items USING hnsw (embedding bit_hamming_ops);
// CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);

const table = pgTable('table', {
    embedding: vector('embedding', { dimensions: 3 })
}, (table) => ({
    l1: index('l1_index').using('hnsw', table.embedding.op('vector_l1_ops'))
    hamming: index('hamming_index').using('hnsw', table.embedding.op('bit_hamming_ops'))
    bit: index('bit_jaccard_index').using('hnsw', table.embedding.op('bit_jaccard_ops'))
}))

For queries, you can use predefined functions for vectors or create custom ones using the SQL template operator.

You can also use the following helpers:

import { l2Distance, l1Distance, innerProduct, 
          cosineDistance, hammingDistance, jaccardDistance } from 'drizzle-orm'

l2Distance(table.column, [3, 1, 2]) // table.column <-> '[3, 1, 2]'
l1Distance(table.column, [3, 1, 2]) // table.column <+> '[3, 1, 2]'

innerProduct(table.column, [3, 1, 2]) // table.column <#> '[3, 1, 2]'
cosineDistance(table.column, [3, 1, 2]) // table.column <=> '[3, 1, 2]'

hammingDistance(table.column, '101') // table.column <~> '101'
jaccardDistance(table.column, '101') // table.column <%> '101'

If pg_vector has some other functions to use, you can replicate implimentation from existing one we have. Here is how it can be done

export function l2Distance(
  column: SQLWrapper | AnyColumn,
  value: number[] | string[] | TypedQueryBuilder<any> | string,
): SQL {
  if (is(value, TypedQueryBuilder<any>) || typeof value === 'string') {
    return sql`${column} <-> ${value}`;
  }
  return sql`${column} <-> ${JSON.stringify(value)}`;
}

Name it as you wish and change the operator. This example allows for a numbers array, strings array, string, or even a select query. Feel free to create any other type you want or even contribute and submit a PR

Examples

Let's take a few examples of pg_vector queries from the pg_vector docs and translate them to Drizzle

import { l2Distance } from 'drizzle-orm';

// SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
db.select().from(items).orderBy(l2Distance(items.embedding, [3,1,2]))

// SELECT embedding <-> '[3,1,2]' AS distance FROM items;
db.select({ distance: l2Distance(items.embedding, [3,1,2]) })

// SELECT * FROM items ORDER BY embedding <-> (SELECT embedding FROM items WHERE id = 1) LIMIT 5;
const subquery = db.select({ embedding: items.embedding }).from(items).where(eq(items.id, 1));
db.select().from(items).orderBy(l2Distance(items.embedding, subquery)).limit(5)

// SELECT (embedding <#> '[3,1,2]') * -1 AS inner_product FROM items;
db.select({ innerProduct: sql`(${maxInnerProduct(items.embedding, [3,1,2])}) * -1` }).from(items)

// and more!

🎉 New PostgreSQL types: point, line

You can now use point and line from PostgreSQL Geometric Types

Type point has 2 modes for mappings from the database: tuple and xy.

• tuple will be accepted for insert and mapped on select to a tuple. So, the database Point(1,2) will be typed as [1,2] with drizzle.

• xy will be accepted for insert and mapped on select to an object with x, y coordinates. So, the database Point(1,2) will be typed as { x: 1, y: 2 } with drizzle

const items = pgTable('items', {
 point: point('point'),
 pointObj: point('point_xy', { mode: 'xy' }),
});

Type line has 2 modes for mappings from the database: tuple and abc.

• tuple will be accepted for insert and mapped on select to a tuple. So, the database Line{1,2,3} will be typed as [1,2,3] with drizzle.

• abc will be accepted for insert and mapped on select to an object with a, b, and c constants from the equation Ax + By + C = 0. So, the database Line{1,2,3} will be typed as { a: 1, b: 2, c: 3 } with drizzle.

const items = pgTable('items', {
 line: line('line'),
 lineObj: point('line_abc', { mode: 'abc' }),
});

🎉 Basic "postgis" extension support

There is no specific code to create an extension inside the Drizzle schema. We assume that if you are using postgis types, indexes, and queries, you have a PostgreSQL database with the postgis extension installed.

geometry type from postgis extension:

const items = pgTable('items', {
  geo: geometry('geo', { type: 'point' }),
  geoObj: geometry('geo_obj', { type: 'point', mode: 'xy' }),
  geoSrid: geometry('geo_options', { type: 'point', mode: 'xy', srid: 4000 }),
});

mode
Type geometry has 2 modes for mappings from the database: tuple and xy.

• tuple will be accepted for insert and mapped on select to a tuple. So, the database geometry will be typed as [1,2] with drizzle.
• xy will be accepted for insert and mapped on select to an object with x, y coordinates. So, the database geometry will be typed as { x: 1, y: 2 } with drizzle

type

The current release has a predefined type: point, which is the geometry(Point) type in the PostgreSQL PostGIS extension. You can specify any string there if you want to use some other type

Drizzle Kit updates: [email protected]

Release notes here are partially duplicated from [email protected]

New Features

🎉 Support for new types

Drizzle Kit can now handle:

• point and line from PostgreSQL
• vector from the PostgreSQL pg_vector extension
• geometry from the PostgreSQL PostGIS extension

🎉 New param in drizzle.config - extensionsFilters

The PostGIS extension creates a few internal tables in the public schema. This means that if you have a database with the PostGIS extension and use push or introspect, all those tables will be included in diff operations. In this case, you would need to specify tablesFilter, find all tables created by the extension, and list them in this parameter.

We have addressed this issue so that you won't need to take all these steps. Simply specify extensionsFilters with the name of the extension used, and Drizzle will skip all the necessary tables.

Currently, we only support the postgis option, but we plan to add more extensions if they create tables in the public schema.

The postgis option will skip the geography_columns, geometry_columns, and spatial_ref_sys tables

import { defineConfig } from 'drizzle-kit'

export default defaultConfig({
  dialect: "postgresql",
  extensionsFilters: ["postgis"],
})

Improvements

Update zod schemas for database credentials and write tests to all the positive/negative cases

• support full set of SSL params in kit config, provide types from node:tls connection

import { defineConfig } from 'drizzle-kit'

export default defaultConfig({
  dialect: "postgresql",
  dbCredentials: {
    ssl: true, //"require" | "allow" | "prefer" | "verify-full" | options from node:tls
  }
})

import { defineConfig } from 'drizzle-kit'

export default defaultConfig({
  dialect: "mysql",
  dbCredentials: {
    ssl: "", // string | SslOptions (ssl options from mysql2 package)
  }
})

Normilized SQLite urls for libsql and better-sqlite3 drivers

Those drivers have different file path patterns, and Drizzle Kit will accept both and create a proper file path format for each

Updated MySQL and SQLite index-as-expression behavior

In this release MySQL and SQLite will properly map expressions into SQL query. Expressions won't be escaped in string but columns will be

export const users = sqliteTable(
  'users',
  {
    id: integer('id').primaryKey(),
    email: text('email').notNull(),
  },
  (table) => ({
    emailUniqueIndex: uniqueIndex('emailUniqueIndex').on(sql`lower(${table.email})`),
  }),
);

-- before
CREATE UNIQUE INDEX `emailUniqueIndex` ON `users` (`lower("users"."email")`);

-- now
CREATE UNIQUE INDEX `emailUniqueIndex` ON `users` (lower("email"));

Bug Fixes

• [BUG]: multiple constraints not added (only the first one is generated) - #​2341
• Drizzle Studio: Error: Connection terminated unexpectedly - #​435
• Unable to run sqlite migrations local - #​432
• error: unknown option '--config' - #​423

How push and generate works for indexes

Limitations

You should specify a name for your index manually if you have an index on at least one expression

Example

index().on(table.id, table.email) // will work well and name will be autogeneretaed
index('my_name').on(table.id, table.email) // will work well

// but

index().on(sql`lower(${table.email})`) // error
index('my_name').on(sql`lower(${table.email})`) // will work well

Push won't generate statements if these fields(list below) were changed in an existing index:

• expressions inside .on() and .using()
• .where() statements
• operator classes .op() on columns

If you are using push workflows and want to change these fields in the index, you would need to:

• Comment out the index
• Push
• Uncomment the index and change those fields
• Push again

For the generate command, drizzle-kit will be triggered by any changes in the index for any property in the new drizzle indexes API, so there are no limitations here.

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