Developing intelligent applications that integrate AI, analytics, and transactional capabilities using the latest release of the world's most popular open-source database
Key Features
Practical examples demonstrating how to use Postgres to develop intelligent applications
Best practices for developers of intelligent data management applications
Includes the latest PostgreSQL 18 features for AI, analytics, and transactions ures for AI, analytics, and transactions
Book DescriptionIn 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.What you will learn
How to leverage PostgreSQL 18 for building intelligent data-driven applications for the modern enterprise
Data management principles and best practices for managing transactions, analytics, and AI use cases
How to utilize Postgres capabilities to address architectural challenges and attain optimal performance for each use case
Methods for utilizing the latest Postgres innovation to create integrated data management applications
Guidelines on when to use Postgres and when to opt for specialized data management solutions
Who this book is forThis book is intended for developers creating intelligent, data-driven applications for the modern enterprise. It features hands-on examples that demonstrate how to use PostgreSQL as the database for business applications that integrate transactions, analytics, and AI. We explore the fundamental architectural principles of data management and detail how developers utilize PostgreSQL 18's latest capabilities to build AI-enabled applications.
The book assumes a working knowledge of SQL and does not address the needs of data analysts or those looking to master SQL.
Sprache
Verlagsort
Maße
Höhe: 235 mm
Breite: 191 mm
ISBN-13
978-1-80602-847-4 (9781806028474)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Marc Linster holds a Ph.D. (Dr. rer. nat) from the University of Kaiserslautern. Marc is the former CTO and Chief Customer Officer of EnterpriseDB (EDB), one of the major contributors to Postgres. At EDB, Marc focused on helping large-scale users understand the art of the possible with Postgres.
Marc has led EDB's product development and services teams for many years, helping customers deploy Postgres at scale and innovate with Postgres. For the last thirteen years, he has been working with Fortune 500 companies to migrate their roadmaps from proprietary software to open-source Postgres. He has given numerous talks at Postgres conferences around the world and discussed Postgres in dozens of webinars. Vibhor Kumar, Global VP at EDB, is a pioneering data tech leader. He manages a global team of engineers, optimizing clients' Postgres databases for peak performance and scalability. He advises Fortune 500 clients, including many Financial Institutes, in innovating and transforming their data platforms. His past experience spans IBM, BMC Software, and CMC Ltd. He holds a BSc in Computer Science from the University of Lucknow and a Master's from the Army Institute of Management. As a certified expert in numerous technologies, he often shares his insights on DevOps, cloud, and database optimization through blogging and speaking at events.
Table of Contents
Transactional, Analytical and AI business systems and their database requirements
The evolution of Postgres to become the number one database for modern applications
A sample eCommerce application
Database requirements for high volume transactional applications
Transactions, ACID compliance, and data normalization
Functions and Stored Procedures
Designing for high transaction volumes and writing efficient transactional code
Doing more with Postgres for transactional applications
Database requirements for analytical use cases
Data modeling for analytics
Analytics functions in Postgres
Views, Materialized Views, Partitions and Indexes
Full text search
Doing more with Postgres for analytical applications
Database requirements for artificial intelligence use cases
Vectors and indexing for AI with pgVector
Combining vectors and standard SQL
Step-by-step approach to integrating LLMs with Postgres to create complete AI applications
Doing more with Postgres for AI
Tying it all together
