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Azure Cosmos DB: SQL API Deep Dive

Azure Cosmos DB: SQL API Deep Dive

1h 1mIntermediate2019-12-12

Authors

Sidney Andrews

Sidney Andrews

Azure MVP and Microsoft Certified Training Regional Lead

Course details

The SQL API is considered the core API for Azure Cosmos DB. It allows developers to query and manage the data they have stored in Cosmos using a familiar programming language. Explore the SQL API more deeply in this course with Microsoft Certified Trainer and Azure MVP Sidney Andrews. Sidney explores the data model and software development kits in SQL API, and then dives straight into writing code to perform common operations in Cosmos DB, such as managing and querying documents. Then he investigates the server side of SQL API, exploring its JavaScript integration and features such as stored procedures. Finally, explore the advanced features of SQL API, such as GeoJSON support for geospatial data and the optimistic concurrency control for resolving server-side conflicts.

Learning objectives
SQL API SDKs
Data model
Managing documents
Querying documents
Server-side programming with SQL API
Creating stored procedures
Storing geospatial data

Skills covered

SQLDatabase DevelopmentDatabase ManagementAzureOpen SourceMicrosoftSoftware DevelopmentDeep Dive (X:Y)

Concepts

0. Introduction

  • 01 - Explore the Azure Cosmos DB SQL API
  • 02 - What you should know

1. Overview of the SQL API

  • 03 - Azure Cosmos DB SQL API
  • 04 - SQL API SDKs
  • 05 - Data model
  • 06 - Data normalization

2. Common Operations

  • 07 - Manage documents
  • 08 - SQL query syntax
  • 09 - Time to live
  • 10 - Challenge - SQL document queries
  • 11 - Solution - SQL document queries

3. Server-Side Programming

  • 12 - Programming in the Data Explorer
  • 13 - Programming in the Data Explorer - Demo
  • 14 - Stored procedures
  • 15 - Advanced stored procedures
  • 16 - Pre- and post-triggers
  • 17 - User-defined functions
  • 18 - Challenge - JavaScript programming
  • 19 - Solution - JavaScript programming

4. Advanced Features

  • 20 - Geospatial data
  • 21 - Optimistic concurrency

Conclusion

  • 22 - Next steps

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