The benefits of semi-structured data in Snowflake

Semi-structured data formats are popular due to their flexibility when working with dynamically varying information. Unlike relational schemas, in which a precise entity structure must be known and fixed ahead of time, semi-structured data is free to include or omit attributes as needed, as long as they are properly nested within corresponding parent objects.

Think of the contact list on your phone. It contains a list of people and their contact details but does not capture those details uniformly. For example, some contacts may contain multiple phone numbers while others have one. Some entries contain information such as an email address and street address, while others have only a number and a vague description in lieu of a name (seriously, who is Green Vespa Laura Friend, and who is Laura?).

To handle this type of data, Snowflake uses the VARIANT data type, which allows semi-structured data to be stored as a column in a relational...