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