JSON in SQL Server 2016

JSON functions in SQL Server enable you to analyze and query JSON data, transform JSON to relational format, and export SQL query results as JSON text.

If you have JSON text, you can extract data from JSON or verify that JSON is properly formatted using built-in functions JSON_VALUE, JSON_QUERY, and ISJSON. For more advanced querying and analysis, the OPENJSON function can transform an array of JSON objects into a set of rows. Any SQL query can be executed on the returned result set. Finally, there is the FOR JSON clause that enables you to format query results as JSON text.

We can start with simple examples. In the following Transact-SQL code, we will define a text variable where we will put JSON text:

Now, we can extract values and objects from JSON text using the JSON_VALUE and JSON_QUERY functions:

This query will return “Basic”, “Bristol”, and ["Sport", "Water polo"] values. The JSON_VALUE function returns one scalar value from JSON text (e.g. strings, numbers, true/false) that is placed on a JSON path specified as the second parameter. JSON_QUERY returns an object or array (in this example an array of tags) on the JSON path. JSON built-in functions use JavaScript-like syntax to reference values and objects in JSON text via second parameter.

The OPENJSON function enables you to reference some array in JSON text and return elements from that array:

Four columns in the result set that is returned by OPENJSON are defined in the WITH clause. OPENJSON will try to find the properties Number, Date, Customer, and Quantity in each JSON object and convert their values into columns in the result set. By default, NULL will be returned if the property is not found. The assumption in the query above is that the @orders variable contains the following JSON array:

As you can see, the transformation from a JSON text to a relational form is simple. You just need to specify column names and types and OPENJSON will find properties in JSON that match these columns. In this example, plain JSON is used; however, OPENJSON can handle any nested/hierarchical structure of JSON objects.

Also, OPENJSON can be used to combine relational and JSON data in the same query. If we assume that the JSON array shown in the previous example is stored in the Orders column, the following query can combine the columns and JSON fields: