Field datatypes
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On this page

    Core datatypes
    Complex datatypes
    Geo datatypes
    Specialised datatypes
    Multi-fields

    Elasticsearch Reference: 

    Getting Started
    Setup
    Breaking changes
    API Conventions
    Document APIs
    Search APIs
    Aggregations
    Indices APIs
    cat APIs
    Cluster APIs
    Query DSL
    Mapping
        Field datatypes
            Array datatype
            Binary datatype
            Boolean datatype
            Date datatype
            Geo-point datatype
            Geo-Shape datatype
            IPv4 datatype
            Nested datatype
            Numeric datatypes
            Object datatype
            String datatype
            Token count datatype
        Meta-Fields
        Mapping parameters
        Dynamic Mapping
        Transform
    Analysis
    Modules
    Index Modules
    Testing
    Glossary of terms
    Release Notes 

Elasticsearch supports a number of different datatypes for the fields in a document:
Core datatypes
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String datatype
    string 
Numeric datatypes
    long, integer, short, byte, double, float 
Date datatype
    date 
Boolean datatype
    boolean 
Binary datatype
    binary 

Complex datatypes
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Array datatype
    Array support does not require a dedicated type 
Object datatype
    object for single JSON objects 
Nested datatype
    nested for arrays of JSON objects 

Geo datatypes
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Geo-point datatype
    geo_point for lat/lon points 
Geo-Shape datatype
    geo_shape for complex shapes like polygons 

Specialised datatypes
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IPv4 datatype
    ip for IPv4 addresses 
Completion datatype
    completion to provide auto-complete suggestions 
Token count datatype
    token_count to count the number of tokens in a string 
mapper-murmur3
    murmur3 to compute hashes of values at index-time and store them in the index 
Attachment datatype
    See the mapper-attachments plugin which supports indexing attachments like Microsoft Office formats, Open Document formats, ePub, HTML, etc. into an attachment datatype. 

Multi-fields
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It is often useful to index the same field in different ways for different purposes. For instance, a string field could be indexed as an analyzed field for full-text search, and as a not_analyzed field for sorting or aggregations. Alternatively, you could index a string field with the standard analyzer, the english analyzer, and the french analyzer.

This is the purpose of multi-fields. Most datatypes support multi-fields via the fields parameter.

Source

https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-types.html