JSON Data Type | JSON Shredding | VantageCloud Lake - JSON Shredding - Teradata Vantage

Vantage allows you shred JSON documents to extract the data and store the extracted data in relational format. The extracted data can be used to insert or update data in existing database tables.

For simple cases of shredding JSON data, you can use the INSERT JSON statement. This statement only supports shredding JSON documents stored in text format.

For more complex cases of shredding JSON data, Vantage provides the following:

JSON_TABLE

This table operator shreds data in a JSON document and creates a derived database table based on the shredded data.

TD_JSONSHRED is recommended for faster shredding of JSON documents that have large numbers of attributes or shred to large numbers of database records.

TD_JSONSHRED

This table operator shreds data in a JSON document, and creates a derived database table based on the shredded data. The operator accepts larger JSON documents and shreds the data significantly more quickly, but does not support the use of JSONPath expressions and supports fewer output data types.

JSON_SHRED_BATCH and JSON_SHRED_BATCH_U

These stored procedures use successive calls to JSON_TABLE to shred multiple JSON documents and create a conglomerate derived database table that can be used to load or update one or more existing database tables.

JSON_SHRED_BATCH operates on LATIN character set data and JSON_SHRED_BATCH_U operates on UNICODE data. Otherwise, the two procedures function identically.

The table operators and stored procedures operate on JSON documents stored in text or binary format.

• Differences between JSON_TABLE and TD_JSONSHRED
• JSON Shredding with INSERT JSON Statement
• JSON_TABLE
• TD_JSONSHRED
• JSON_SHRED_BATCH and JSON_SHRED_BATCH_U