AI-Ready PostgreSQL 18

Building Intelligent Data Systems with Transactions, Analytics, and Vectors

Created by Vibhor Kumar, Marc Linster

Explore how to use PostgreSQL 18 to build intelligent, high-performance data systems that combine transactions, analytics, and AI. Learn to design modern applications that deliver real-time insights and automation using the latest features and proven strategies.

Packt | Apr 2026 | 580 min

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LevelIntermediate

CategoriesData Engineering, Data Warehousing and Big Data Processing Frameworks, PostgreSQL, SQL

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

What You Will Learn

You will work through practical, real-world examples that show how to combine transactional, analytical, and AI capabilities in PostgreSQL 18. Guided by industry experts, you will gain hands-on experience applying best practices and advanced techniques to solve common data challenges.

Key Features

Apply PostgreSQL 18 features for AI, analytics, and transactional workloads
Design unified architectures for real-time data-driven applications
Optimize performance and scalability for enterprise-grade solutions

Target Audience

Ideal for backend developers, data engineers, and architects with a basic understanding of SQL and relational databases. If you want to design high-performance systems, implement analytics, and add AI features like vector search to your apps, you will find actionable guidance and clear strategies here.

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