JSON is a semi-structured data format. It can be used in a multitude of applications, but it has become more common as a format for data transmission between servers and web applications or web connected devices. This is partially because those applications can often only receive data as text, and JSON is a text based data format.
In comparison to flat files like CSVs, which use relational “columns and rows”, JSON files store data in nested Objects and Arrays, which themselves contain values. This structure is highly adaptable to the addition of new data, meaning that the collection of data doesn’t need to be limited by the columns within the datasource.
Analytics for for SEMI-Structured DATA with Snowflake
Snowflake is unusual in that it can natively support JSON (and other semi-structured data) alongside relational data. Most databases and data stores only support one format. With Snowflake, users can choose to “flatten” nested objects into a relational table, or store the Objects and Arrays in their native format within the VARIANT data type. Semi-structured data can be manipulated with ANSI-standard SQL, with the addition of dot notation.
To learn more, check out our video, Processing JSON data in Snowflake