1. Developer Intro to Cosmos DB

2. About Me Brandon Brockhoeft
BIO
Brandon is a career software engineer working primarily with Microsoft solutions with over 15 years of professional experience. He has provided development and architecture technology solutions in the finance, state government, energy, and aerospace industries. His functional expertise includes: full-stack development, distributed architecture, real-time communication, DevOps and agile transformation, & mentoring.
Brandon Brockhoeft
Principal Consultant
@bbrockhoeft22
brandon-brockhoeft-55777a1

3. What is Cosmos DB? Globally distributed, multi-model DB Azure service
Schema-less (Code is the schema!)
Transparently replicates data
Multi-master writes
Consistency choices
Automatic indexing
SQL and NoSQL APIs
Changefeed (CEP)

4. DB Usage Comparison Cosmos DB SQL Server Scale Horizontal Vertical
Data
Geo-Distributed / Eventual Consistency
Integrity and Consistency Focused
Cost
Throughput and Storage-based
CPU-based
Tooling
Microsoft and Dev Community
Microsoft and Commercial Products

5. Cosmos DB Setup Containers and Partitions Partition Keys
Request units: item size, indexing, property count, consistency, query patterns
RU/s = $ Cost
Insufficient funds = throttled requests

6. Indexing
Cosmos DB automatically indexes every property for all items in your container
Indexing done synchronously when data is written
Indexes are written as trees used to map to property paths: /locations/1/country: "France"
Customize indexing by setting its indexing mode & include/exclude property paths
Order by multiple properties requires custom composite indexes
Index transformation done online and in-place: impacts query consistency

7. Tools Cosmos DB Data Migration Tool
Build / Download:
Documentation:
Manage and automate Cosmos DB resources:
PowerShell
Azure CLI
Azure Resource Manager templates
Work with data (using SQL)
Cosmos DB Playground:
Document Explorer - Azure or Local Emulator

8. Data Modeling Code-first at all times
Performing w/o a net: little constraints, no cascading, few DB types, no sizes, or defaults
Have well-defined and tested validation patterns
Mistakes not as easily corrected* (as SQL Server)
Self-joins only in SQL API
Unique key constraints only within partition
Implies document ID is not the partition ID
Can be single property or composite key
Cannot be changed; requires new container + data migration
Modeling techniques:
Embed data (denormalized)
Reference data (normalized)
Hybrid

9. Data Modeling - Embed
All within one JSON document - allows single read/write
Duplication of data is okay
Typically better read performance
Useful when:
Contained relationships between entities
One-to-few relationships between entities
Embedded data that changes infrequently
Embedded data that will not grow without bound
Embedded data that is queried frequently together {
"id": "1",
"firstName": "Thomas",
"lastName": "Andersen",
"addresses": [
"line1": "100 Some Street",
"line2": "Unit 1",
"city": "Seattle",
"state": "WA",
"zip": 98012 } ],
"contactDetails": [
{" ":
{"phone": " "} ]

10. Data Modeling - Reference
No foreign-keys / weak links only
Requires multiple database trips
Don’t create join containers
Typically better write performance
Consider data growth for relationship
Useful when:
Representing one-to-many relationships
Representing many-to-many relationships
Related data changes frequently
Referenced data could be unbounded
Author documents:
{"id": "a1", "name": "Thomas Andersen", "books": ["b1, "b2", "b3"]}
{"id": "a2", "name": "William Wakefield", "books": ["b1", "b4"]}
Book documents:
{"id": "b1", "name": "Azure Cosmos DB 101", "authors": ["a1", "a2"]}
{"id": "b2", "name": "Azure Cosmos DB for RDBMS Users", "authors": ["a1"]}
{"id": "b3", "name": "Learn about Azure Cosmos DB", "authors": ["a1"]}
{"id": "b4", "name": "Deep Dive into Azure Cosmos DB", "authors": ["a2"]}

11. Data Modeling - Hybrid Author documents: Book documents: { "id": "a1",
"firstName": "Thomas",
"lastName": "Andersen",
"countOfBooks": 3,
"books": ["b1", "b2", "b3"],
"images": [
{"thumbnail": "
{"profile": "
{"large": " ] },
"id": "a2",
"firstName": "William",
"lastName": "Wakefield",
"countOfBooks": 1,
"books": ["b1"], }
Book documents: {
"id": "b1",
"name": "Azure Cosmos DB 101",
"authors": [
{"id": "a1", "name": "Thomas Andersen", "thumbnailUrl": "
{"id": "a2", "name": "William Wakefield", "thumbnailUrl": " ] },
"id": "b2",
"name": "Azure Cosmos DB for RDBMS Users",
{"id": "a1", "name": "Thomas Andersen", "thumbnailUrl": " }

12. Sample Azure Data Explorer
SQL Query examples - see CosmosDemo/CustomerContact/docs/SQL_Samples.md
Customer Contact Demo application with C# SDK (v3)
ASP.NET sample app with form data

13. More Info Conference video on Cosmos DB by Jimmy Bogard
Microsoft documentation (Used for presentation content)
Microsoft dotnet SDK reference
Query cheat sheets

14. Session Evaluations
Session Evaluations are ONLINE ONLY. Your feedback is valuable!
SQLSatBR.com/Sessions/SessionEvaluation.aspx

15. Changefeed Event Driven Architecture by default
Lambda Architecture with low TCO
Use Azure Functions without infrastructure concerns
Observe container changes sorted within partition key
Consumer parallel processing available by partition key
Use soft markers for data operation filtering (insert/update/delete)
Consider use of TTL and start time options

16. Data Modeling - Mixed Types
Book and Review documents in one container: {
"id": "b1",
"name": "Azure Cosmos DB 101",
"bookId": "b1",
"type": "book" },
"id": "r1",
"content": "This book is awesome",
"type": "review"
"id": "r2",
"content": "Best book ever!", }