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Book Overview & Buying
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Table Of Contents
AI-Ready PostgreSQL 18
By :
AI-Ready PostgreSQL 18
By:
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)
Preface
Part 1: Introducing PostgreSQL and Setting the Stage
Chapter 1: Transactional, Analytical, and AI Business Systems and Their Database Requirements
Chapter 2: The Evolution of Postgres
Chapter 3: A Sample E-Commerce Application
Part 2: Creating Transactional Applications
Chapter 4: Database Requirements for High-Volume Transactional Applications
Chapter 5: Transactions, ACID Compliance, and Data Normalization
Chapter 6: Functions and Stored Procedures
Chapter 7: Designing for High Transaction Volumes and Writing Efficient Transactional Code
Chapter 8: Understanding and Monitoring Transactional Application Performance
Part 3: Creating Analytical Applications
Chapter 9: Database Requirements for Analytical Use Cases
Chapter 10: The Analytics Data Model
Chapter 11: Feeding the PostgreSQL Data Warehouse
Chapter 12: Transforming the Data for Analytics
Chapter 13: PostgreSQL's Analytics Functions
Chapter 14: Analyzing Text Documents in PostgreSQL
Part 4: Using PostgreSQL as an AI Platform
Chapter 15: Database Requirements for Artificial Intelligence Use Cases
Chapter 16: Vectors and Indexing for AI with pgvector
Chapter 17: Multi-Modal Reasoning: Combining AI Vectors with Standard SQL
Chapter 18: Step-by-Step Approach to Integrating LLMs with PostgreSQL to Create Complete AI Applications
Chapter 19: Production-Ready AI Embedding Pipeline Patterns
Chapter 20: PostgreSQL and MCP: The Blueprint for a Robust AI Assistant
Chapter 21: Tying It All Together
Chapter 22: Unlock Access to the Code Bundle and the PDF Version
Index

