What is the difference between BigQuery's JSON type and Snowflake's VARIANT type?

BigQuery JSON and Snowflake VARIANT serve similar purposes with different implementations. BigQuery JSON stores data in columnar format, enabling efficient field-level scanning and compression. Snowflake VARIANT uses self-describing format optimized for semi-structured data. BigQuery JSON integrates with SQL using JSON functions (JSON_EXTRACT, JSON_VALUE). Snowflake uses path notation with colon syntax: variant_col:field::type. BigQuery requires explicit type casting in queries. Snowflake VARIANT handles integers, strings, objects, arrays, booleans, and null natively. BigQuery JSON is a dedicated type; Snowflake VARIANT also handles XML and other formats. BigQuery optimizes storage by column; Snowflake optimizes by clustering paths. Both support nested access, but syntax differs significantly. BigQuery JSON queries cost based on data scanned. Snowflake VARIANT queries cost based on compute time. Test your JSON structures with our JSON Editor at jsonconsole.com/json-editor when migrating between platforms. Both provide production-grade semi-structured data support. Choose based on existing platform investment and query patterns. Neither has clear superiority—both excel in their ecosystems.