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  • Book Overview & Buying AI-Ready PostgreSQL 18
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AI-Ready PostgreSQL 18

AI-Ready PostgreSQL 18

By : Vibhor Kumar, Marc Linster
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AI-Ready PostgreSQL 18

AI-Ready PostgreSQL 18

By: Vibhor Kumar, Marc Linster

Overview of this book

In today’s data-first world, businesses need applications that blend transactions, analytics, and AI to power real-time insights at scale. Mastering PostgreSQL 18 for AI-Powered Enterprise Apps is your essential guide to building intelligent, high-performance systems with the latest features of PostgreSQL 18. Through hands-on examples and expert guidance, you’ll learn to design architectures that unite OLTP and OLAP, embed AI directly into apps, and optimize for speed, scalability, and reliability. Discover how to apply cutting-edge PostgreSQL tools for real-time decisions, predictive analytics, and automation. Go beyond basics with advanced strategies trusted by industry leaders. Whether you’re building data-rich applications, internal analytics platforms, or AI-driven services, this book equips you with the patterns and insights to deliver enterprise-grade innovation. Ideal for developers, architects, and tech leads driving digital transformation, this book empowers you to lead the future of intelligent applications. Harness the power of PostgreSQL 18—and unlock the full potential of your data.
Table of Contents (28 chapters)
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1
Part 1: Introducing PostgreSQL and Setting the Stage
5
Part 2: Creating Transactional Applications
11
Part 3: Creating Analytical Applications
18
Part 4: Using PostgreSQL as an AI Platform
27
Index

Summary

Transactions and ACID compliance are key to reliable modern enterprise systems. PostgreSQL provides many tools to manage transactions and control the level of ACID compliance, so that the developer can make informed trade-offs between performance and application complexity.

While controlling and managing transactions is key to reliability, data modeling is essential to performance. A normalized data model avoids redundancy, increases performance, and simplifies query design.

In this chapter, you learned how to define transactions, how to control their execution and rollback, and how to choose the correct isolation level for an application. We also walked step by step through the data normalization process to help you create data models that avoid redundancy and undesirable internal dependencies.

In the next chapter, we will dive into the details of the PostgreSQL data types and indexes that you should use to create the data models and achieve high performance.

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AI-Ready PostgreSQL 18
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