You're reading from Limitless Analytics with Azure Synapse An end-to-end analytics service for data processing, management, and ingestion for BI and ML

Product type Paperback

Published in Jun 2021

Publisher Packt

ISBN-13 9781800205659

Length 392 pages

Edition 1st Edition

Languages

Python

Tools

Azure

Concepts

Data Processing

Authors (2):

Saranya Ravichander

Prashant Kumar Mishra

View More author details

Table of Contents (20) Chapters

Preface

1. Section 1: The Basics and Key Concepts

2. Chapter 1: Introduction to Azure Synapse FREE CHAPTER

3. Chapter 2: Considerations for Your Compute Environment

4. Section 2: Data Ingestion and Orchestration

5. Chapter 3: Bringing Your Data to Azure Synapse

6. Chapter 4: Using Synapse Pipelines to Orchestrate Your Data

7. Chapter 5: Using Synapse Link with Azure Cosmos DB

8. Section 3: Azure Synapse for Data Scientists and Business Analysts

9. Chapter 6: Working with T-SQL in Azure Synapse

10. Chapter 7: Working with R, Python, Scala, .NET, and Spark SQL in Azure Synapse

11. Chapter 8: Integrating a Power BI Workspace with Azure Synapse

12. Chapter 9: Perform Real-Time Analytics on Streaming Data

13. Chapter 10: Generate Powerful Insights on Azure Synapse Using Azure ML

14. Section 4: Best Practices

15. Chapter 11: Performing Backup and Restore in Azure Synapse Analytics

16. Chapter 12: Securing Data on Azure Synapse

17. Chapter 13: Managing and Monitoring Synapse Workloads

18. Chapter 14: Coding Best Practices

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Data storage

A Cosmos DB analytical store is fully isolated from transactional workloads. The operational data in a Cosmos DB container is internally stored in row-based transactional stores in order to allow fast transactional reads and writes.

It is not recommended to run complex queries on your transactional workload – it may cause bad performance for your application running these queries. Ideally, you should add an analytical data layer on top of Cosmos DB transactional data if you want to perform complex operations on the data. The major caveat for this architecture is an ETL operation for data sync between transactional and analytical data stores. This additional step may lead to increased Total Cost of Operation (TCO) and overhead of maintaining the data in sync always.

With this new feature of Synapse Link, Cosmos DB gives you the flexibility to enable an analytical store within your Cosmos DB account without performing an ETL operation. Both the data layers are...