NoSQL database have grown popularity in recent years due to the flexibility of data modeling and scaling up capabilities. NoSQL database also have been using in big data landscape. The demo rich session will elaborate difference between SQL and NoSQL.

1. SQL vs. NoSQL
(looking at NoSQL database from the view of a SQL
database professional)

2. Father and
Husband
Blogger
Data
Engineer
Diverse
background
Community
Twitter: @Paulswengrr
Blog: www.allaboutdata.ca

3. What we
cover
Refresh our memory with traditional SQL
Know about NoSQL (MongoDB)
Demo
Comparison

4. SQL Syntax
SELECT Id, Product, Price
From Product
Where ProductCategory=’Bikes’
Join, Insert, Update, Delete

5. Schema
CREATE TABLE [Production].[Product](
[ProductID] [int] IDENTITY(1,1) NOT NULL,
[Name] [nvarchar](100) NOT NULL,
[ProductNumber] [nvarchar](25) NOT NULL,
[MakeFlag] [dbo].[Flag] NOT NULL,
[FinishedGoodsFlag] [dbo].[Flag] NOT NULL,
[Color] [nvarchar](15) NULL,
[SafetyStockLevel] [smallint] NOT NULL,
[StandardCost] [money] NOT NULL,
[ListPrice] [money] NOT NULL,
[Size] [nvarchar](5) NULL)

6. Relationship/Normalization
Customer Bridge table (Order)
Product
Id Name Price Description
1 “Mountain Bike “ 2500 “Bike for mountain trek”
2 “City Bike” 1000 “Best fit to roam around city”
Id Customer_ID Product_ID
1 2 1
2 2 2
3 1 1
Id Name Email
1 Morten
Sorenson
m.s@outlook.com
2 Andersen Lu al@yahoo.com
3 Derek Paul dp@outlook.com

7. Type of relationships

8. NoSQL
• MongoDB
• Azure Cosmos DB
• Amazon Document DB
• Oracle NoSQL
• Google BigTable

9. NoSQL- MongoDB
“MongoDB” derives from the word “humongous”

10. Database E-Commerce
Collections Table –Customer, Product…
Documents {“Name”: ”Anders”, age:36}
{“Name”: “Carsten”, age:42}

11. No Schema
Id:1 Age:36Name: ‘Anders’ …..
Id:2
Age:36
Name: ‘Carsten’ …..
Id:3 …..

12. NoSQL –No relation
Profession
{id:1,profession:’Developer’}
{id:2, profession: ’Data Engineer’}
{id:3, profession: ’Actor’}
Users
{id:1,name:’Tom Hanks’, age:20}
{id:2,name:’Casper Ruther’, age:42}
{id:3,name:’Paul Anders’, age:63}
db.Users.insert(
{
id:"01",
name:"Tom Hanks",
age:20
email:"th@hollywood.com",
Profession:["Developer","Data
Engineer","Actor"]
}
)
Usersprofession
{id:1,userId:1,professionId:1}
{id:2,userId:1, professionId: 2}
{id:3,userId: 1, professionId: 3}
{id:4,userId: 2, professionId: 2}

13. Tools: MongoDB
https://www.mongodb.com/products/compass
Robo 3T: https://robomongo.org/
https://docs.mongodb.com/manual/core/data-model-design/
https://docs.mongodb.com/manual/reference/method/db.collection.update/

14. Languages
• MONGO SHELL
• Python
• java
• C#
• Scala
• GO and many more.

15. Demo

16. SQL vs NoSQL
SQL NoSQL
Data uses Schema Schema-less (Schema Agnostic)
Maintain Relationship No relations– though you can design relationship
Data distributed in multiple tables Data in one table (embedded)
Monolithic, you can easily Scale-Up. Scale out is also
possible but difficult (e.g. Azure Elastic
Database tools)
Scale up and scale out- Globally distributed