Indexes (Prisma ORM v7) (/docs/orm/v7/prisma-schema/data-model/indexes)

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How to configure index functionality and add full text indexes

Location: ORM > v7 > Prisma Schema > Data Model > Indexes

Prisma ORM allows configuration of database indexes, unique constraints and primary key constraints. Full text indexes in MySQL and MongoDB are available through the fullTextIndex preview feature using the @@fulltext attribute.

You can configure indexes, unique constraints, and primary key constraints with the following attribute arguments:

• The length argument allows you to specify a maximum length for the subpart of the value to be indexed on String and Bytes types

  • Available on the @id, @@id, @unique, @@unique and @@index attributes
  • MySQL only

• The sort argument allows you to specify the order that the entries of the constraint or index are stored in the database

  • Available on the @unique, @@unique and @@index attributes in all databases, and on the @id and @@id attributes in SQL Server

• The type argument allows you to support index access methods other than PostgreSQL's default BTree access method

  • Available on the @@index attribute
  • PostgreSQL only
  • Supported index access methods: Hash, Gist, Gin, SpGist and Brin

• The clustered argument allows you to configure whether a constraint or index is clustered or non-clustered

  • Available on the @id, @@id, @unique, @@unique and @@index attributes
  • SQL Server only

• The map argument allows you to specify a custom name for the index or constraint in the underlying database

  • Available on the @id, @@id, @unique, @@unique and @@index attributes
  • Supported in all databases

The length argument is specific to MySQL and allows you to define indexes and constraints on columns of String and Byte types. For these types, MySQL requires you to specify a maximum length for the subpart of the value to be indexed in cases where the full value would exceed MySQL's limits for index sizes. See the MySQL documentation for more details.

The length argument is available on the @id, @@id, @unique, @@unique and @@index attributes.

As an example, the following data model declares an id field with a maximum length of 3000 characters:

model Id {
  id String @id @db.VarChar(3000)
}

This is not valid in MySQL because it exceeds MySQL's index storage limit and therefore Prisma ORM rejects the data model. The generated SQL would be rejected by the database.

CREATE TABLE `Id` (
  `id` VARCHAR(3000) PRIMARY KEY
)

The length argument allows you to specify that only a subpart of the id value represents the primary key. In the example below, the first 100 characters are used:

model Id {
  id String @id(length: 100) @db.VarChar(3000)
}

Prisma Migrate is able to create constraints and indexes with the length argument if specified in your data model. This means that you can create indexes and constraints on values of Prisma schema type Byte and String. If you don't specify the argument the index is treated as covering the full value as before.

Introspection will fetch these limits where they are present in your existing database. This allows Prisma ORM to support indexes and constraints that were previously suppressed and results in better support of MySQL databases utilizing this feature.

The length argument can also be used on compound primary keys, using the @@id attribute, as in the example below:

model CompoundId {
  id_1 String @db.VarChar(3000)
  id_2 String @db.VarChar(3000)

  @@id([id_1(length: 100), id_2(length: 10)])
}

A similar syntax can be used for the @@unique and @@index attributes.

The sort argument allows you to specify the order that the entries of the index or constraint are stored in the database. This can have an effect on whether the database is able to use an index for specific queries. The behavior and support varies by database:

• In MySQL/MariaDB, you can specify sort order (ASC/DESC) directly in unique constraints and indexes
• In PostgreSQL, sort order can only be specified on indexes, not on unique constraints
• In SQL Server, sort order is supported on all constraints and indexes including @id and @@id

For example, in MySQL/MariaDB, the following table using a descending unique constraint:

CREATE TABLE `Unique` (
  `unique` INT,
  CONSTRAINT `Unique_unique_key` UNIQUE (`unique` DESC)
)

would be introspected as

model Unique {
  unique Int @unique(sort: Desc)
}

Note that in PostgreSQL, while you cannot specify sort order on unique constraints directly, you can create a unique index with a sort order that will enforce uniqueness:

-- PostgreSQL approach
CREATE UNIQUE INDEX "unique_index_desc" ON "Unique" ("unique" DESC);

The sort argument can also be used on compound indexes:

model CompoundUnique {
  unique_1 Int
  unique_2 Int

  @@unique([unique_1(sort: Desc), unique_2])
}

The following example demonstrates the use of the sort and length arguments to configure indexes and constraints for a Post model:

model Post {
  title      String   @db.VarChar(300)
  abstract   String   @db.VarChar(3000)
  slug       String   @unique(sort: Desc, length: 42) @db.VarChar(3000)
  author     String
  created_at DateTime

  @@id([title(length: 100, sort: Desc), abstract(length: 10)])
  @@index([author, created_at(sort: Desc)])
}

The type argument is available for configuring the index type in PostgreSQL with the @@index attribute. The index access methods available are Hash, Gist, Gin, SpGist and Brin, as well as the default BTree index access method.

The Hash type will store the index data in a format that is much faster to search and insert, and that will use less disk space. However, only the = and <> comparisons can use the index, so other comparison operators such as < and > will be much slower with Hash than when using the default BTree type.

As an example, the following model adds an index with a type of Hash to the value field:

model Example {
  id    Int @id
  value Int

  @@index([value], type: Hash)
}

This translates to the following SQL commands:

CREATE TABLE "Example" (
  id INT PRIMARY KEY,
  value INT NOT NULL
);

CREATE INDEX "Example_value_idx" ON "Example" USING HASH (value);

The GIN index stores composite values, such as arrays or JsonB data. This is useful for speeding up querying whether one object is part of another object. It is commonly used for full-text searches.

An indexed field can define the operator class, which defines the operators handled by the index.

[!WARNING] Indexes using a function (such as to_tsvector) to determine the indexed value are not yet supported by Prisma ORM. Indexes defined in this way will not be visible with prisma db pull.

As an example, the following model adds a Gin index to the value field, with JsonbPathOps as the class of operators allowed to use the index:

model Example {
  id    Int  @id
  value Json
  //    ^ field type matching the operator class

  @@index([value(ops: JsonbPathOps)], type: Gin)
  //                  ^ operator class      ^ index type
}

This translates to the following SQL commands:

CREATE TABLE "Example" (
  id INT PRIMARY KEY,
  value JSONB NOT NULL
);

CREATE INDEX "Example_value_idx" ON "Example" USING GIN (value jsonb_path_ops);

As part of the JsonbPathOps the @> operator is handled by the index, speeding up queries such as value @> '{"foo": 2}'.

Prisma ORM generally supports operator classes provided by PostgreSQL in versions 10 and later. If the operator class requires the field type to be of a type Prisma ORM does not yet support, using the raw function with a string input allows you to use these operator classes without validation.

The default operator class (marked with ✅) can be omitted from the index definition.

Read more about built-in operator classes in the official PostgreSQL documentation.

GIN and BTree are the only index types supported by CockroachDB. The operator classes marked to work with CockroachDB are the only ones allowed on that database and supported by Prisma ORM. The operator class cannot be defined in the Prisma Schema Language: the ops argument is not necessary or allowed on CockroachDB.

The GiST index type is used for implementing indexing schemes for user-defined types. By default there are not many direct uses for GiST indexes, but for example the B-Tree index type is built using a GiST index.

As an example, the following model adds a Gist index to the value field with InetOps as the operators that will be using the index:

model Example {
  id    Int    @id
  value String @db.Inet
  //           ^ native type matching the operator class
  //                                   ^ index type
  //                  ^ operator class

  @@index([value(ops: InetOps)], type: Gist)
}

This translates to the following SQL commands:

CREATE TABLE "Example" (
  id INT PRIMARY KEY,
  value INET NOT NULL
);

CREATE INDEX "Example_value_idx" ON "Example" USING GIST (value inet_ops);

Queries comparing IP addresses, such as value > '10.0.0.2', will use the index.

Prisma ORM generally supports operator classes provided by PostgreSQL in versions 10 and later. If the operator class requires the field type to be of a type Prisma ORM does not yet support, using the raw function with a string input allows you to use these operator classes without validation.

Read more about built-in operator classes in the official PostgreSQL documentation.

The SP-GiST index is a good choice for many different non-balanced data structures. If the query matches the partitioning rule, it can be very fast.

As with GiST, SP-GiST is important as a building block for user-defined types, allowing implementation of custom search operators directly with the database.

As an example, the following model adds a SpGist index to the value field with TextOps as the operators using the index:

model Example {
  id    Int    @id
  value String
  //    ^ field type matching the operator class

  @@index([value], type: SpGist)
  //                     ^ index type
  //       ^ using the default ops: TextOps
}

This translates to the following SQL commands:

CREATE TABLE "Example" (
  id INT PRIMARY KEY,
  value TEXT NOT NULL
);

CREATE INDEX "Example_value_idx" ON "Example" USING SPGIST (value);

Queries such as value LIKE 'something%' will be sped up by the index.

Prisma ORM generally supports operator classes provided by PostgreSQL in versions 10 and later. If the operator class requires the field type to be of a type Prisma ORM does not yet support, using the raw function with a string input allows you to use these operator classes without validation.

The default operator class (marked with ✅) can be omitted from the index definition.

Read more about built-in operator classes from official PostgreSQL documentation.

The BRIN index type is useful if you have lots of data that does not change after it is inserted, such as date and time values. If your data is a good fit for the index, it can store large datasets in a minimal space.

As an example, the following model adds a Brin index to the value field with Int4BloomOps as the operators that will be using the index:

model Example {
  id    Int @id
  value Int
  //    ^ field type matching the operator class

  @@index([value(ops: Int4BloomOps)], type: Brin)
  //                  ^ operator class      ^ index type
}

This translates to the following SQL commands:

CREATE TABLE "Example" (
  id INT PRIMARY KEY,
  value INT4 NOT NULL
);

CREATE INDEX "Example_value_idx" ON "Example" USING BRIN (value int4_bloom_ops);

Queries like value = 2 will now use the index, which uses a fraction of the space used by the BTree or Hash indexes.

Prisma ORM generally supports operator classes provided by PostgreSQL in versions 10 and later, and some supported operators are only available from PostgreSQL versions 14 and later. If the operator class requires the field type to be of a type Prisma ORM does not yet support, using the raw function with a string input allows you to use these operator classes without validation.

The default operator class (marked with ✅) can be omitted from the index definition.

Read more about built-in operator classes in the official PostgreSQL documentation.

The clustered argument is available to configure (non)clustered indexes in SQL Server. It can be used on the @id, @@id, @unique, @@unique and @@index attributes.

As an example, the following model configures the @id to be non-clustered (instead of the clustered default):

model Example {
  id    Int @id(clustered: false)
  value Int
}

This translates to the following SQL commands:

CREATE TABLE [Example] (
  id INT NOT NULL,
  value INT,
  CONSTRAINT [Example_pkey] PRIMARY KEY NONCLUSTERED (id)
)

The default value of clustered for each attribute is as follows:

A table can have at most one clustered index.

The map argument allows you to specify a custom name for the index or constraint in the underlying database. This is useful when you want to use a specific naming convention or when the auto-generated name doesn't meet your requirements.

The map argument is available on the @id, @@id, @unique, @@unique and @@index attributes.

As an example, the following model configures a custom name for the index on the title field:

model Post {
  id    Int    @id
  title String

  @@index([title], map: "my_custom_index_name")
}

This translates to the following SQL command (PostgreSQL example):

CREATE INDEX "my_custom_index_name" ON "Post" ("title");

Without the map argument, Prisma would generate a default name like Post_title_idx.

The map argument can also be used on unique constraints:

model User {
  id    Int    @id
  email String @unique(map: "unique_user_email")
}

And on composite indexes and constraints:

model Post {
  id        Int    @id
  title     String
  author    String
  createdAt DateTime

  @@index([author, createdAt], map: "posts_author_date_idx")
  @@unique([title, author], map: "posts_title_author_unique")
}

The where argument allows you to define partial indexes (also known as filtered indexes). A partial index only includes rows that match a specified condition, which reduces the index size and improves both write performance and query performance for the indexed subset of data.

The where argument is available on the @unique, @@unique and @@index attributes. It requires the partialIndexes Preview feature.

[!NOTE] Partial indexes are supported on PostgreSQL, SQLite, SQL Server, and CockroachDB. They are not supported on MySQL.

To use partial indexes, add the partialIndexes feature flag to the generator block of your schema.prisma file:

generator client {
  provider        = "prisma-client"
  output          = "./generated"
  previewFeatures = ["partialIndexes"]
}

You can define a partial index with a raw SQL predicate string using the raw() function. This approach supports any valid SQL WHERE expression that your database accepts:

model User {
  id        Int       @id
  email     String
  status    String
  deletedAt DateTime?

  @@unique([email], where: raw("status = 'active'"))
  @@index([email], where: raw("\"deletedAt\" IS NULL"))
}

This generates SQL like:

PostgreSQL:

CREATE UNIQUE INDEX "User_email_key" ON "User" ("email") WHERE (status = 'active');
CREATE INDEX "User_email_idx" ON "User" ("email") WHERE ("deletedAt" IS NULL);

SQLite:

CREATE UNIQUE INDEX "User_email_key" ON "User" ("email") WHERE status = 'active';
CREATE INDEX "User_email_idx" ON "User" ("email") WHERE "deletedAt" IS NULL;

SQL Server:

CREATE UNIQUE NONCLUSTERED INDEX [User_email_key] ON [dbo].[User]([email]) WHERE ([status]='active');
CREATE NONCLUSTERED INDEX [User_email_idx] ON [dbo].[User]([email]) WHERE ([deletedAt] IS NULL);

The raw() syntax can be used with any SQL expression your database supports, making it the most flexible option.

You can also define partial indexes using an object literal syntax, which provides type-safety by validating field names and value types against your Prisma schema:

model Post {
  id        Int      @id
  title     String
  published Boolean

  @@index([title], where: { published: true })
  @@unique([title], where: { published: true })
}

The object literal syntax supports the following value types:

You can combine multiple conditions in a single object:

model User {
  id        Int       @id
  email     String
  active    Boolean
  deletedAt DateTime?

  @@unique([email], where: { active: true, deletedAt: null })
}

[!NOTE] The object literal syntax validates field types. For example, you cannot use a Boolean value for a String field. For fields with types that are not supported by the object syntax (such as Unsupported or composite types), use raw() instead.

The where argument can be combined with other index arguments such as name and map:

model User {
  id     Int    @id
  email  String
  status String

  @@unique([email], name: "email_active_unique", map: "idx_email_active", where: raw("status = 'active'"))
}

[!WARNING] CockroachDB limitation: CockroachDB supports creating partial indexes, but it cannot introspect the predicate text from existing indexes. This means that after initial creation, modifications to the where clause (adding, changing, or removing a predicate) will not be detected by Prisma Migrate. The differ skips predicate comparison for CockroachDB to prevent false-positive migrations.

When you run prisma db pull on a database that contains partial indexes, Prisma ORM will:

1. Automatically add "partialIndexes" to the previewFeatures list in your generator block
2. Represent the partial index predicate using the raw() syntax with the database's normalized form of the SQL expression

For example, a PostgreSQL partial unique index on a single field will be introspected as:

model User {
  id     Int    @id
  email  String @unique(where: raw("(status = 'active'::text)"))
  status String
}

[!NOTE] The introspected raw() string reflects the database's normalized form of the SQL expression, which may differ from what you originally wrote. For example, PostgreSQL adds parentheses and explicit type casts (e.g., 'active'::text), SQL Server wraps column names in brackets and adds parentheses (e.g., ([status]='active')), while SQLite generally preserves the original expression as-is.

The fullTextIndex preview feature provides support for introspection and migration of full text indexes in MySQL and MongoDB. This can be configured using the @@fulltext attribute. Existing full text indexes in the database are added to your Prisma schema after introspecting with db pull, and new full text indexes added in the Prisma schema are created in the database when using Prisma Migrate.

[!WARNING] For now we do not enable the full text search commands in Prisma Client for MongoDB; the progress can be followed in the MongoDB issue.

To enable the fullTextIndex preview feature, add the fullTextIndex feature flag to the generator block of the schema.prisma file:

generator client {
  provider        = "prisma-client"
  output          = "./generated"
  previewFeatures = ["fullTextIndex"]
}

The following example demonstrates adding a @@fulltext index to the title and content fields of a Post model:

model Post {
  id      Int    @id
  title   String @db.VarChar(255)
  content String @db.Text

  @@fulltext([title, content])
}

On MongoDB, you can use the @@fulltext index attribute (via the fullTextIndex preview feature) with the sort argument to add fields to your full-text index in ascending or descending order. The following example adds a @@fulltext index to the title and content fields of the Post model, and sorts the title field in descending order:

generator js {
  provider        = "prisma-client-js"
  previewFeatures = ["fullTextIndex"]
}

datasource db {
  provider = "mongodb"
  url      = env("DATABASE_URL")
}

model Post {
  id      String @id @map("_id") @db.ObjectId
  title   String
  content String

  @@fulltext([title(sort: Desc), content])
}

• Database mapping: Learn how to map model and field names to database tables and columns
• External tables: How to declare and use externally managed tables in Prisma ORM
• Models: Learn about the concepts for building your data model with Prisma: Models, scalar types, enums, attributes, functions, IDs, default values and more
• Multi-schema: How to use Prisma ORM with multiple database schemas
• Relations: A relation is a connection between two models in the Prisma schema. This page explains how you can define one-to-one, one-to-many and many-to-many relations in Prisma