What Is Data Type in Elasticsearch?


Larry Thompson

In Elasticsearch, a data type is a way to specify the type of data that can be stored in a field. Each field in an Elasticsearch document has a specific data type associated with it. Understanding data types is essential for efficient indexing and searching in Elasticsearch.

Why are Data Types Important?

Data types play a crucial role in Elasticsearch because they determine how values are indexed and stored internally. By explicitly defining the data type for each field, Elasticsearch can optimize storage and perform more accurate searches.

Common Data Types in Elasticsearch

Text Data Types

Elasticsearch provides several text-specific data types:

  • Text: This is the default text data type. It is suitable for full-text search and supports tokenization, stemming, and other text analysis techniques.
  • Keyword: Keyword fields are not analyzed and are used for structured search, sorting, and aggregations.

Numeric Data Types

Elasticsearch offers various numeric data types:

  • Integer: Integers represent whole numbers without fractional parts.
  • Long: Longs are used to store large numbers that exceed the range of integers.
  • Float: Floats store single-precision floating-point numbers.
  • Double: Doubles represent double-precision floating-point numbers.

Date Data Types

Date fields store dates or timestamps. Elasticsearch supports two date formats:

  • Date: Dates without time components (e.g., “2021-12-31”).
  • Date With Time: Dates with time components (e., “2021-12-31T23:59:59”).

Boolean Data Type

The boolean data type can only have two values: true or false. It is used for boolean operations, filtering, and querying.

Binary Data Type

The binary data type is used to store binary data, such as images or serialized objects. It is typically used for advanced use cases.

Specifying Data Types in Elasticsearch Mapping

In Elasticsearch, you can specify the data type for each field in the index’s mapping. The mapping defines the structure and characteristics of the fields in your documents.

To explicitly define a field’s data type, you can use the properties section in the mapping definition. For example:

  "mappings": {
    "properties": {
      "name": {
        "type": "text"
      "age": {
        "type": "integer"

In this example, the name field has a text data type, while the age field has an integer data type. By explicitly defining these types, Elasticsearch can optimize storage and searching operations.

In Conclusion

Data types are essential in Elasticsearch as they determine how values are indexed and stored internally. By choosing the appropriate data types for your fields and explicitly specifying them in the mapping, you can ensure efficient indexing and accurate search results.

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