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Database Design and Modeling with Google Cloud

Database Design and Modeling with Google Cloud

By : Sukumaran
4.9 (7)
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Database Design and Modeling with Google Cloud

Database Design and Modeling with Google Cloud

4.9 (7)
By: Sukumaran

Overview of this book

In the age of lightning-speed delivery, customers want everything developed, built, and delivered at high speed and at scale. Knowledge, design, and choice of database is critical in that journey, but there is no one-size-fits-all solution. This book serves as a comprehensive and practical guide for data professionals who want to design and model their databases efficiently. The book begins by taking you through business, technical, and design considerations for databases. Next, it takes you on an immersive structured database deep dive for both transactional and analytical real-world use cases using Cloud SQL, Spanner, and BigQuery. As you progress, you’ll explore semi-structured and unstructured database considerations with practical applications using Firestore, cloud storage, and more. You’ll also find insights into operational considerations for databases and the database design journey for taking your data to AI with Vertex AI APIs and generative AI examples. By the end of this book, you will be well-versed in designing and modeling data and databases for your applications using Google Cloud.
Table of Contents (18 chapters)
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1
Part 1:Database Model: Business and Technical Design Considerations
4
Part 2:Structured Data
8
Part 3:Semi-Structured, Unstructured Data, and NoSQL Design
11
Part 4:DevOps and Databases
13
Part 5:Data to AI

Summary

In this chapter, we explored semi-structured data and its fundamental aspects, real-world use cases, and design considerations. Semi-structured data, characterized by its adaptability and hierarchical nature, bridges the gap between structured and unstructured data, making it an invaluable resource in today’s data-driven landscape.

We then talked about NoSQL databases, which are designed to handle semi-structured and unstructured data efficiently. These databases prioritize robust design, flexibility, and high availability. We explored the principles of consistency, availability, and partition tolerance, which are crucial for distributed data stores.

Firestore, a serverless document database, stood out as a prime example of a NoSQL database. Its features, including scalability, strong consistency, and multi-region replication, make it a top choice for various applications. The chapter also shed light on Firestore’s data model, indexing techniques, and collection...

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