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

19. Other Books You May Enjoy

Chapter 2: Considerations for Your Compute Environment

This chapter covers the analytics runtimes available with Azure Synapse. You will learn about the concepts of SQL Pool, SQL on-demand, and Spark pool. After completing this chapter, you will be able to decide which analytics runtime will be suitable for solving your business problem.

SQL Pool and SQL on-demand are both part of the Structured Query Language (SQL) engine, but they differ in terms of provisioning. When you create a SQL pool, you will provision databases under a logical server in your subscription; this means you will be paying for running the SQL engine all the time until SQL pool is paused. However, SQL on-demand is created when you want to leverage the SQL engine for running your workloads only for a short duration.

On the other hand, Spark pool works with the Apache Spark engine, deeply integrated with Azure Synapse. This gives you the option to configure your Spark pool with just a few clicks, along with...