Book Image

Modern Data Architecture on AWS

By : Behram Irani
5 (1)
Book Image

Modern Data Architecture on AWS

5 (1)
By: Behram Irani

Overview of this book

Many IT leaders and professionals are adept at extracting data from a particular type of database and deriving value from it. However, designing and implementing an enterprise-wide holistic data platform with purpose-built data services, all seamlessly working in tandem with the least amount of manual intervention, still poses a challenge. This book will help you explore end-to-end solutions to common data, analytics, and AI/ML use cases by leveraging AWS services. The chapters systematically take you through all the building blocks of a modern data platform, including data lakes, data warehouses, data ingestion patterns, data consumption patterns, data governance, and AI/ML patterns. Using real-world use cases, each chapter highlights the features and functionalities of numerous AWS services to enable you to create a scalable, flexible, performant, and cost-effective modern data platform. By the end of this book, you’ll be equipped with all the necessary architectural patterns and be able to apply this knowledge to efficiently build a modern data platform for your organization using AWS services.
Table of Contents (24 chapters)
1
Part 1: Foundational Data Lake
5
Part 2: Purpose-Built Services And Unified Data Access
17
Part 3: Govern, Scale, Optimize And Operationalize

Data federation using Amazon Redshift

Federated queries can be executed even from inside Redshift, allowing Redshift data to be joined with data from relational data sources such as PostgreSQL and MySQL, either on Amazon RDS or on Amazon Aurora. For certain use cases, it does not make sense to spend time creating an ETL pipeline to load data inside Redshift. Redshift can connect to these sources and distribute the execution of such queries down to the data source itself to improve performance.

The following figure highlights the current data sources that Redshift federated queries can work with. With the federated architecture in place inside Redshift, more source connectors may get added in the future, to expand the ecosystem and broaden the use cases that can be solved with this architecture pattern:

Figure 9.7 – Redshift federated queries

Figure 9.7 – Redshift federated queries

Amazon Redshift federated queries use case

To understand this better, let’s consider a use case...