1. Let's make a complex dataset simple using Azure Cosmos DB
Hansamali Gamage
Senior Engineer (TIQRI) ● Blogger ● Speaker ● Traveler
Let's make a complex dataset simple using Azure Cosmos DB

2. Azure Cosmos DB

3. Azure Cosmos DB Not a database, It’s a database service
Low latency
Multi model & Multi API support
Global Distribution
Elastic scale out
Multiple data models & APIs
Global distribution
Scaling throughput & storage
Service level agreements
Comprehensive SLAs

4. Why Azure CosmosDB
Difference in Azure SQL database vs Azure Cosmos DB

5. Partitioning & Global Distribution
R/W R
South East Asia
Product Category = ‘A’
Product Category = ‘B’
Product Category = ‘C’ R
R/W
Central US
Data partitioning and sectioning
Product catalog
Fail over regions R
R/W
East Europe

6. Consistency vs Availability vs Response Time
Data Distribution
Consistency
Availability
Can’t achieve both Data availability & consistency
Shopping cart application
Consistency levels
Session consistency
Change consistency programmatically

7. Scale throughput and storage
Low response time
Per application requirements
Scale throughput & storage
Throughout in seconds and minutes
If host in a physical server
Per second & per minute granularities

8. RU (Request Units) & Pricing
RU is the Currency
Control RU when you scale your apps
RU is the currency
Based on the calculations need to process the request
Remodel your database
Throttled database requests
Notifcation for throttled requests
calculated based on the computation per request

9. Cosmos DB is a database service
Azure Cosmos DB
Cosmos DB is a database service
Key - value
Column family
Documents
Graph DB

10. Azure Document API De-normalized data Document is a JSON object
Flexible schema
Azure Document API
De-normalized data
Stores data in documents
Document is a JSON object
Can have mixed data in a document
Data stored as documents
JSON object
Data types in Document API
Referential Integrity
Referential integrity is not enforced

11. Database Schema & Index Management in Document API
Schema free
Scheme free
Automatically indexed all the paths
Properties automatically indexed

12. Modeling data for a document database
Data modeling is important as in a relational DB
Important
Enforcement of schema is a need by the developers

13. Are You Non-relational

14. ORM
Normalized data
What you store is what you get

15. Modeling the data in relational way
Order
Order Item
Customer
Product

16. Modeling the data in document way
Order
Id (key)
Customer
Items
Item
Product
Item
Product

17. Embed or Reference

18. Embed vs Reference

19. DEMO

20. Connect the dots You can try it yourself, check this article,
Azure Cosmos DB: Designing your data structure

21. Thank you hansamaligamage@gmail.com
@hansamaligamage