JSON has become the standard format for transmitting serialized data in today's websites, APIs, and applications. With SQL Server 2016, Microsoft has made it easy to work with JSON strings in T-SQL. This session is an introduction to the new JSON functions added in SQL Server 2016. We will use T-SQL query examples to learn how these new functions can be used to parse, create, and modify JSON data. We will also discuss when it's appropriate to store JSON in databases as well as how to optimize performance when using these new functions. By the end of this presentation DBAs and developers will know how to efficiently work with JSON data in SQL Server 2016.

1. JSON Usage and
Performance in
SQL Server 2016
NEO SQL Server User Group | Bert Wagner | April 4, 2017
1

3. Background
● BI developer at Progressive Insurance for 6+ years
● I love JSON - I use it in APIs, hardware projects, websites
● I also love SQL and relational database structures
● Slide, demos, code is available on bertwagner.com
3

4. Overview
● What is JSON?
● Why use JSON?
● When is it appropriate to store JSON in SQL?
● Usage examples:
○ ETL and reporting
○ Database object maintenance
○ Performance parsing
4

5. 5
What does JSON look like?
{
“Make” : “Volkswagen”,
“Year” : 2003,
“Model” : {
“Base” : “Golf”,
“Trim” : “GL”
},
“Colors” : [“White”, “Pearl”, “Rust”],
“PurchaseDate” : “2006-10-05T00:00:00.000Z”
}

6. 6
Why use JSON?
Easy Processing
var car = { "Make" : "Volkswagen" };
console.log(car.Make);
// Output: Volkswagen
car.Year = 2003;
console.log(car);
// Output: { "Make" : "Volkswagen", "Year" : 2003" }
Javascript:

7. 7
Why use JSON?
APIs

8. 8
Why use JSON?
Storage Size
<Car>
<Make>Volkswagen</Make>
<Year>2003</Year>
<Model>
<Base>Golf</Base>
<Trim>GL</Trim>
</Model>
<Colors>
<Color>White</Color>
<Color>Pearl</Color>
<Color>Rust</Color>
</Colors>
<PurchaseDate>
2006-10-05 00:00:00.000
</PurcaseDate>
</Car>
{
“Make” : “Volkswagen”,
“Year” : 2003,
“Model” : {
“Base” : “Golf”,
“Trim” : “GL”
},
“Colors” :
[“White”, “Pearl”, Rust”],
“PurchaseDate” :
“2006-10-05T00:00:00.000Z”
}
XML: 225 Characters JSON: 145 Characters

9. 9
Appropriate Usage
Staging Data
● Load data raw
● Validate
● Transform

10. 10
Appropriate Usage
Error Logging
ErrorDate Component Data
2016-03-17 21:23:39 GetInventory { "Make : "Volkswagen", "Year" : 2003}
2016-03-19 12:59:31 Login { "User" : "Bert", "Referrer" : "http://google.com",
"AdditionalDetails" : "Invalid number of login attempts" }

11. 11
Appropriate Usage
Non-Analytical Data
● Sessions
● User preferences
● Non-frequently changing variables
○ Admin emails
○ Static dropdown menus

12. 12
Inappropriate Usage
High-Performance Requirements

13. 13
Inappropriate Usage
Validation/Integrity Requirements

14. 14
Inappropriate Usage
Being Lazy

15. Demos
1. ETL and reporting
2. Database object maintenance
3. Performance parsing
15

16. Performance Results
16
● Indexes on computed columns are the solution
● Faster than C# libraries in some cases

17. Recap
17
● Many good (and bad) uses for JSON in SQL exist
● JSON can be fully manipulated in SQL Server 2016
● Performance is fast, especially with computed
column indexes

18. Thank you!
● Twitter: @bertwagner
● Blog: https://bertwagner.com
● Email: bertwagner@bertwagner.com
18