![]() J.SalesOrderID, J.OrderDate, J.SubTotal, J.TaxAmt, J.TotalDue As for each Customer it can contain multiple orders we will get multiple rows for each Customer and multiple columns as per defined in the JSON string:Ĭ.BusinessEntityID, C.FirstName, C.MiddleName, C.LastName, C.EmailPromotion, –> Let’s Query back the JSON data from the OrderDetailsJSON column with other columns in relational form, by using OPENJSON() function. –> Check the above inserted records with the OrderDetailsJSON column containing data in JSON format: ( SELECT SalesOrderID, OrderDate, SubTotal, TaxAmt, TotalDueįROM. We will use FOR JSON AUTO option to convert relational data to JSON string for our example, as shown below:īusinessEntityID, FirstName, MiddleName, LastName, EmailPromotion, –> Let’s create a sample record-set with JSON data in OrderDetailsJSON column. OrderDetailsJSON NVARCHAR(MAX) - normal column with NVARCHAR datatypeĬHECK ( IsJSON ( OrderDetailsJSON ) = 1 ) - CHECK Constraint to validate JSON string –> Ok, now let’s create a new Table with OrderDetailsJSON column for storing JSON string with a CHECK constraint on it: You can download AdvantureWorks2014 sample Database from Microsoft. ![]() from level 120 to 130, like:ĪLTER DATABASE SET COMPATIBILITY_LEVEL = 130 IsJSON() function: can be used as a CHECK constraint on the columns that contain JSON string which will validate if the JSON string is in proper format or not.Īs we will need AdvantureWorks2014 Sample Database in our example below, we need to upgrade its Compatibility from SQL 2014 to SQL 2016, i.e. But to store JSON data there is no new datatype introduced, JSON can be stored in an NVARCHAR datatype column just like a plain text, and to validate it you can add a CHECK constraint on it. XML data is stored in a column of XML datatype which also check the validity of the XML data to be stored. Here, in this post I’ll show how we can store JSON data in a normal table column, just like you store XML data. In my previous posts I talked about how to a Table or Query data into JSON string format, and from JSON string to Relational-table format, and with.
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