This document discusses using JSON in SQL Server. It begins with background on the author and an overview of topics to be covered. The document then defines what JSON is, why it would be used, and when it is appropriate to store JSON in SQL. Examples of using JSON for ETL, reporting, and database object maintenance are provided. Performance comparisons are shown between JSON, XML, and .NET. The document concludes that JSON can be fully manipulated in SQL Server 2016 and is preferable to XML for new projects, especially with improvements in SQL Server 2017.

1. DBAs vs Developers:
JSON in SQL Server
| Bert Wagner | March 8, 2018
1

3. Background
• BI developer @ Progressive Insurance for 6+ years
• I ❤ JSON – I use it in APIs, hardware projects, websites
• I also ❤ SQL – relational database structures
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
• Performance comparisons
4
Demo code and slides available at bertwagner.com

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 w/ computed column indexes
4. SQL JSON vs XML vs .NET performance comparisons
15

16. Performance Results - XML
16
• JSON faster in almost all categories
• If considering entire app performance, maybe faster in
all categories

17. Performance Results - .NET
17
• Competitive with C# libraries
• Indexes on computed columns are BLAZING!

18. 18
JSON – What’s new in SQL Server 2017?
• Clustered column store indexes support nvarchar(max)
• Compression
• Faster (maybe)
• In memory-optimized tables
• Computed columns
• All JSON functions supported

19. Recap
19
• Many good (and bad) uses for JSON in SQL exist
• JSON can be fully manipulated in SQL Server 2016
• JSON is preferable to XML for new projects
• JSON performance is comparable to .NET, faster with
computed column indexes

20. Thank you!
@bertwagner
bertwagner.com
youtube.com/c/bertwagner
bert@bertwagner.com
20
New posts and
videos every
Tuesday!

21. 21
Appendix
Software for keeping screen region on top
• On Top Replica
Blog posts and YouTube videos:
• SQL Server JSON Usage - Parsing
• SQL Server JSON Usage - Creating
• SQL Server JSON Usage - Updating, Adding, Deleting
• Performance Comparisons - .NET
• Performance Comparisons - XML
• Performance Comparisons - .NET and XML Redux
• JSON Computed Column Indexes
• Jovan Popovic’s JSON posts
Microsoft Connect
• Add an option to JSON_MODIFY() to fully delete values from arrays