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Data Lakehouse in Action

You're reading from   Data Lakehouse in Action Architecting a modern and scalable data analytics platform

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Product type Paperback
Published in Mar 2022
Publisher Packt
ISBN-13 9781801815932
Length 206 pages
Edition 1st Edition
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Author (1):
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Pradeep Menon Pradeep Menon
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Pradeep Menon
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Table of Contents (14) Chapters Close

Preface 1. PART 1: Architectural Patterns for Analytics
2. Chapter 1: Introducing the Evolution of Data Analytics Patterns FREE CHAPTER 3. Chapter 2: The Data Lakehouse Architecture Overview 4. PART 2: Data Lakehouse Component Deep Dive
5. Chapter 3: Ingesting and Processing Data in a Data Lakehouse 6. Chapter 4: Storing and Serving Data in a Data Lakehouse 7. Chapter 5: Deriving Insights from a Data Lakehouse 8. Chapter 6: Applying Data Governance in the Data Lakehouse 9. Chapter 7: Applying Data Security in a Data Lakehouse 10. PART 3: Implementing and Governing a Data Lakehouse
11. Chapter 8: Implementing a Data Lakehouse on Microsoft Azure 12. Chapter 9: Scaling the Data Lakehouse Architecture 13. Other Books You May Enjoy

Storing data in the data serving layer

Once the data is processed in the data lake, it needs to be served to the downstream applications or stakeholders. The following figure shows the interaction between different data lake layers and the data serving layer:

Figure 4.7 – The interaction of other data lake layers with the data serving layer

Let's investigate the different datastores that we can use in the data serving layer to enable these services.

The following figure maps how the different datastores can be utilized using different technologies:

Figure 4.8 – Mapping the data serving layer to different technologies

Now, let's move on to cover SQL-based serving.

SQL-based serving

Relational Database Management Systems (RDBMSes) have been used to store structured data for many decades. They still have their place in the context of modern data analytics. Structured Query Language (SQL), the language...

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