![]() Each table was pasted into Excel and tidied up. Just as a side-note, this data was collected for this article in various places on the internet but mainly from Yan Tan Tethera. ![]() We will start off by creating a simple table that we want to import into. Converting Simple JSON Arrays of Objects to Table-sources You will need access to SQL Server version, 2016 and later or Azure SQL Database or Warehouse to play along and you can download data and code from GitHub. I don’t use Sheep-counting words because they are of general importance but because they can be used to represent whatever data you are trying to import. The simple aim is to put them into a table. We’ll start by using the example of sheep-counting words, collected from many different parts of Great Britain and Brittany. We’ll then try slightly trickier JSON documents with embedded arrays and so on. Let’s start this gently, putting simple collections into strings which we will insert into a table. Once those are in place we’ll then import a single JSON Document, filling the ten tables with the data of 70,000 fake records from it. In this article we’ll start simply and work through a couple of sample examples before ending by creating a SQL server database schema with ten tables, constraints and keys. Fortunately, schema-less data collections are rare. If each of the documents have different schemas, then you have little chance. ![]() It is fairly easy to Import JSON collections of documents into SQL Server if there is an underlying ‘explicit’ table schema available to them.
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