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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

Vector databases

As I promised, let me brief you a little about vector databases. I have taken the approach of explaining it to a 10-year-old; you can skip to the last paragraph of this section if you are not comfortable with this explanation.

Imagine that you have a big box of toys. Each toy has many different features, such as its shape, color, size, and material. You could describe each toy in words, but that would be very time-consuming and difficult to search through. A vector database is a way to represent each toy as a set of numbers, called a vector. Each number in the vector represents a different feature of the toy.

For example, the first number might represent the toy’s shape, the second number might represent its color, and so on. Vector databases are very efficient for searching. For example, you could search for all the toys that are red and ball-shaped. The vector database would simply compare the vectors of all of the toys to find the ones that match your...

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