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Field and type options

Available field types and options.

Redis Open Source provides various field types that allow you to store and search different kinds of data in your indexes. This page explains the available field types, their characteristics, and how they can be used effectively.

Numeric fields

Numeric fields are used to store non-textual, countable values. They can hold integer or floating-point values. Numeric fields are sortable, meaning you can perform range-based queries and retrieve documents based on specific numeric conditions. For example, you can search for documents with a price between a certain range or retrieve documents with a specific rating value.

You can add number fields to a schema in FT.CREATE using this syntax:

FT.CREATE ... SCHEMA ... {field_name} NUMERIC [SORTABLE] [NOINDEX]

where:

You can search for documents with specific numeric values using the @<field_name>:[<min> <max>] query syntax. For example, this query finds documents with a price between 200 and 300:

FT.SEARCH products "@price:[200 300]"

You can also use the following query syntax to perform more complex numeric queries:

Comparison operator

Query string

Comment

min <= x <= max

@field:[min max]

Fully inclusive range

"@field>=min @field<=max"

Fully inclusive range *

min < x < max

@field:[(min (max]

Fully exclusive range

"@field>min @field<max"

Fully exclusive range *

grouping with a space denotes AND relationship

x >= min

@field:[min +inf]

Upper open range

@field>=min

Upper open range *

x <= max

@field:[-inf max]

Lower open range

@field<=max

Lower open range *

x == val

@field:[val val]

Equal

@field:[val]

Equal *

@field==val

Equal *

x != val

-@field:[val val]

Not equal

@field!=val

Not equal *

x == val1 or x == val2

"@field==val1 | @field==val2"

Grouping with a bar denotes OR relationship *

* New syntax as of RediSearch v2.10. Requires DIALECT 2.

Geo fields

Geo fields are used to store geographical coordinates such as longitude and latitude. They enable geospatial radius queries, which allow you to implement location-based search functionality in your applications such as finding nearby restaurants, stores, or any other points of interest.

Redis Search also supports geoshape fields for more advanced geospatial queries. See the Geospatial reference page for an introduction to the format and usage of both schema types.

You can add geo fields to the schema in FT.CREATE using this syntax:

FT.CREATE ... SCHEMA ... {field_name} GEO [SORTABLE] [NOINDEX]

Where:

You can query geo fields using the @<field_name>:[<lon> <lat> <radius> <unit>] query syntax. For example, this query finds documents within 1000 kilometers from the point 2.34, 48.86:

FT.SEARCH cities "@coords:[2.34 48.86 1000 km]"

See Geospatial queries for more information and code examples.

Geoshape fields

Geoshape fields provide more advanced functionality than Geo. You can use them to represent locations as points but also to define shapes and query the interactions between points and shapes (for example, to find all points that are contained within an enclosing shape). You can also choose between geographical coordinates (on the surface of a sphere) or standard Cartesian coordinates. Use geoshape fields for spatial queries such as finding all office locations in a specified region or finding all rooms in a building that fall within range of a wi-fi router.

See the Geospatial reference page for an introduction to the format and usage of both the geoshape and geo schema types.

Add geoshape fields to the schema in FT.CREATE using the following syntax:

FT.CREATE ... SCHEMA ... {field_name} GEOSHAPE [FLAT|SPHERICAL] [NOINDEX]

Where:

Note that unlike geo fields, geoshape fields don't support the SORTABLE option.

Query geoshape fields using the syntax @<field_name>:[<OPERATION> <shape>] where <operation> is one of WITHIN, CONTAINS, INTERSECTS, or DISJOINT, and <shape> is the shape of interest, specified in the Well-known text format. For example, the query below finds shapes that contain the point (2, 2):

FT.SEARCH idx "(@geom:[CONTAINS $qshape])" PARAMS 2 qshape "POINT (2 2)" RETURN 1 name DIALECT 2

See Geospatial queries for more information and code examples.

Vector fields

Vector fields are floating-point vectors that are typically generated by external machine learning models. These vectors represent unstructured data such as text, images, or other complex features. Redis allows you to search for similar vectors using vector search algorithms like cosine similarity, Euclidean distance, and inner product. This enables you to build advanced search applications, recommendation systems, or content similarity analysis.

You can add vector fields to the schema in FT.CREATE using this syntax:

FT.CREATE ... SCHEMA ... {field_name} VECTOR {algorithm} {count} [{attribute_name} {attribute_value} ...]

Where:

For more information about vector fields, see vector fields.

Tag fields

Tag fields are used to store textual data that represents a collection of data tags or labels. Tag fields are characterized by their low cardinality, meaning they typically have a limited number of distinct values. Unlike text fields, tag fields are stored as-is without tokenization or stemming. They are useful for organizing and categorizing data, making it easier to filter and retrieve documents based on specific tags.

Tag fields can be added to the schema with the following syntax:

FT.CREATE ... SCHEMA ... {field_name} TAG [SEPARATOR {sep}] [CASESENSITIVE]

where

You can search for documents with specific tags using the @<field_name>:{<tag>} query syntax. For example, this query finds documents with the tag blue:

FT.SEARCH idx "@tags:{blue}"

For more information about tag fields, see Tag Fields.

Text fields

Text fields are specifically designed for storing human language text. When indexing text fields, Redis performs several transformations to optimize search capabilities. The text is transformed to lowercase, allowing case-insensitive searches. The data is tokenized, meaning it is split into individual words or tokens, which enables efficient full-text search functionality. Text fields can be weighted to assign different levels of importance to specific fields during search operations. Additionally, text fields can be sorted based on their values, enabling the sorting of search results by relevance or other criteria.

Text fields can be added to the schema with the following syntax:

FT.CREATE ... SCHEMA ... {field_name} TEXT [WEIGHT] [NOSTEM] [PHONETIC {matcher}] [SORTABLE] [NOINDEX] [WITHSUFFIXTRIE]

where

You can search for documents with specific text values using the <term> or the @<field_name>:{<term>} query syntax. Here are a couple of examples:

Unicode considerations

Redis Search only supports Unicode characters in the basic multilingual plane; U+0000 to U+FFFF. Unicode characters beyond U+FFFF, such as Emojis, are not supported and would not be retrieved by queries including such characters in the following use cases:

Examples:

redis> FT.CREATE idx SCHEMA tag TAG text TEXT
OK
redis> HSET doc:1 tag '😀😁🙂' text '😀😁🙂'
(integer) 2
redis> HSET doc:2 tag '😀😁🙂abc' text '😀😁🙂abc'
(integer) 2
redis> FT.SEARCH idx '@text:(*😀😁🙂)' NOCONTENT
1) (integer) 0
redis> FT.SEARCH idx '@text:(*😀😁🙂*)' NOCONTENT
1) (integer) 0
redis> FT.SEARCH idx '@text:(😀😁🙂*)' NOCONTENT
1) (integer) 0

redis> FT.SEARCH idx '@text:(%😀😁🙃%)' NOCONTENT
1) (integer) 0

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