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PostgreSQL 18 for Developers

You're reading from   PostgreSQL 18 for Developers Crafting flexible and intelligent data-driven solutions for today's enterprise

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Product type Paperback
Published in Apr 2026
Publisher Packt
ISBN-13 9781806028474
Length 379 pages
Edition 1st Edition
Languages
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Authors (2):
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Marc Linster Marc Linster
Author Profile Icon Marc Linster
Marc Linster
Vibhor Kumar Vibhor Kumar
Author Profile Icon Vibhor Kumar
Vibhor Kumar
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PostgreSQL 18 for Developers: Crafting flexible and intelligent data-driven solutions for today’s enterprise

Welcome to Packt Early Access. We’re giving you an exclusive preview of this book before it goes on sale. It can take many months to write a book, but our authors have cutting-edge information to share with you today. Early Access gives you an insight into the latest developments by making chapter drafts available. The chapters may be a little rough around the edges right now, but our authors will update them over time.You can dip in and out of this book or follow along from start to finish; Early Access is designed to be flexible. We hope you enjoy getting to know more about the process of writing a Packt book.

  1. Chapter 1: Transactional, Analytical and AI business systems and their database requirements
  2. Chapter 2: The evolution of Postgres to become the number one database for modern applications
  3. Chapter 3: A sample eCommerce application
  4. Chapter 4: Database requirements for high volume transactional applications
  5. Chapter 5: Doing more with Postgres for transactional applications
  6. Chapter 6: Transactions, ACID compliance, and data normalization
  7. Chapter 7: Functions and Stored Procedures
  8. Chapter 8: Designing for high transaction volumes and writing efficient transactional code
  9. Chapter 9: Doing more with Postgres for transactional applications
  10. Chapter 10: Database requirements for analytical use cases
  11. Chapter 11: Data modeling for analytics
  12. Chapter 12: Analytics functions in Postgres
  13. Chapter 13: Views, Materialized Views, Partitions and Indexes
  14. Chapter 14: Full text search
  15. Chapter 15: Doing more with Postgres for analytical applications
  16. Chapter 16: Database requirements for artificial intelligence use cases
  17. Chapter 17: Vectors and indexing for AI with pgVector
  18. Chapter 18: Combining vectors and standard SQL
  19. Chapter19: Step-by-step approach to integrating LLMs with Postgres to create complete AI applications
  20. Chapter20: Doing more with Postgres for AI
  21. Chapter21: Tying it all together
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PostgreSQL 18 for Developers
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