From the course: Snowflake SnowPro Core Cert Prep

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Working with semi-structured data

Working with semi-structured data - Snowflake Tutorial

From the course: Snowflake SnowPro Core Cert Prep

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Working with semi-structured data

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Now, one key distinction from other database technologies with Snowflake is that you can store semi-structured data directly in its native format, such as JSON, for example, in a relational table column. And to do this, Snowflake has introduce a special type of data known as a variant. This allows you to insert JSON, AVRO, Parquet, ORC, or XML data directly into that field without needing to tell Snowflake what the format of this data is upfront. Just make sure for the exam that you keep in mind the five different types of semi-structured data Snowflake supports. We covered some of these in the data loading and unloading module earlier on in this course. And just note that the maximum length of a variant column is 16 MB. That could come up in the certification as one of the questions. So in this example, we're creating a new table with one variant column. Just be aware that we could have other columns which are standard relational data types such as character fields or number fields…

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