![]() ![]() Performance for operations on relational data and data in a VARIANT column is very similar. ![]() If data was loaded from JSON format and stored in VARIANT, then the following guideline(s) apply:įor data that is mostly regular and uses only native JSON types (strings and numbers, not timestamps), both storage and query VARIANT null is a true value that compares as equal to itself. Represent a null value in semi-structured data. SELECT 'Sample', 'Sample' ::VARIANT, 'Sample' ::VARIANT::VARCHAR + -+-+-+ | 'SAMPLE' | 'SAMPLE'::VARIANT | 'SAMPLE'::VARIANT::VARCHAR | |-+-+-| | Sample | "Sample" | Sample | + -+-+-+Ī VARIANT value can be missing (contain SQL NULL), which is different from a VARIANT null value, which is a real value used to JSON, Avro, ORC, Parquet, or XML).Įach of these data types is described below. Which can be used to load and operate on data in semi-structured formats (e.g. However, combining these data types allows you toĮxplicitly represent arbitrary hierarchical data structures, Strictly speaking, OBJECT is the only one of theseĭata types that, by itself, has all of the characteristics of a true We often refer to these data types as semi-structured data types. OBJECT (can directly contain VARIANT, and thus indirectly contain any other data type, including itself). VARIANT (can contain any other data type).ĪRRAY (can directly contain VARIANT, and thus indirectly contain any other data type, including itself). The following Snowflake data types can contain other data types: Supported Formats for Semi-structured DataĬonsiderations for Semi-structured Data Stored in VARIANT ![]()
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