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Azure Synapse Analytics Cookbook

You're reading from   Azure Synapse Analytics Cookbook Implement a limitless analytical platform using effective recipes for Azure Synapse

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Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781803231501
Length 238 pages
Edition 1st Edition
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Authors (2):
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Gaurav Agarwal(BLR) Gaurav Agarwal(BLR)
Author Profile Icon Gaurav Agarwal(BLR)
Gaurav Agarwal(BLR)
Meenakshi Muralidharan Meenakshi Muralidharan
Author Profile Icon Meenakshi Muralidharan
Meenakshi Muralidharan
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Table of Contents (11) Chapters Close

Preface 1. Chapter 1: Choosing the Optimal Method for Loading Data to Synapse 2. Chapter 2: Creating Robust Data Pipelines and Data Transformation FREE CHAPTER 3. Chapter 3: Processing Data Optimally across Multiple Nodes 4. Chapter 4: Engineering Real-Time Analytics with Azure Synapse Link Using Cosmos DB 5. Chapter 5: Data Transformation and Processing with Synapse Notebooks 6. Chapter 6: Enriching Data Using the Azure ML AutoML Regression Model 7. Chapter 7: Visualizing and Reporting Petabytes of Data 8. Chapter 8: Data Cataloging and Governance 9. Chapter 9: MPP Platform Migration to Synapse 10. Other Books You May Enjoy

Integrating an Azure Synapse ETL pipeline with Cosmos DB

In this section, we will understand Azure Synapse Link for Cosmos DB and its usage for real-time analytics. We will learn about the following topics:

  • The basics of Cosmos DB
  • Azure Synapse Link integration with Cosmos DB
  • Feature support of Cosmos DB with Synapse
  • Synapse runtime support
  • Structured streaming support
  • Security features of Cosmos DB

Introducing Cosmos DB

Azure Cosmos DB is a fully isolated columnar store for large-scale analytics with operational data and a transactional store that is schema-agnostic, which allows us to use it with transactional applications without the overhead of managing schema or indexes.

Azure Cosmos DB analytical store is optimized for use for analytical workloads, which offers good analytical query performance.

When operational data is stored in a transaction store in row store format, analytical queries would be expensive, since we need provisioned...

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