{"product_id":"postgresql-18-for-automated-ai-pipelines-automate-embedding-optimize-vector-search-and-scale-your-data-architecture-with-confidence-9798258982049","title":"PostgreSQL 18 for Automated AI Pipelines: Automate Embedding, Optimize Vector Search, and Scale Your Data Architecture with Confidence","description":"\u003cp\u003e • Author(s): Stan Bird\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Database Administration \u0026amp; Management\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eUnlock the full potential of your AI systems, without the complexity of fragmented tools.\u003c\/p\u003e\u003cp\u003e\u003cb\u003e\u003ci\u003ePostgreSQL 18 for Automated AI Pipelines\u003c\/i\u003e\u003c\/b\u003e is a hands-on, production-focused guide that shows you how to build scalable, secure, and fully automated AI data architectures directly inside PostgreSQL. If you're tired of juggling vector databases, brittle ETL pipelines, and costly cloud dependencies, this book offers a powerful alternative: a unified, database-centric approach to modern AI engineering.\u003c\/p\u003e\u003cp\u003eDesigned for software engineers, data architects, and backend developers, this book walks you step-by-step through creating \u003cb\u003eAI-native pipelines\u003c\/b\u003e that automate embedding generation, optimize vector search, and power high-performance Retrieval-Augmented Generation (RAG) systems. You'll learn how to store, index, and query high-dimensional embeddings alongside relational data-eliminating synchronization issues and ensuring consistent, real-time intelligence.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eInside, you'll discover how to: \u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eBuild automated embedding pipelines using triggers, background workers, and in-database orchestration\u003c\/li\u003e\n\u003cli\u003eImplement pgvector and pgvectorscale for high-speed, scalable vector search\u003c\/li\u003e\n\u003cli\u003eDesign robust schemas for machine learning and RAG workloads\u003c\/li\u003e\n\u003cli\u003eCreate hybrid search systems that combine semantic and keyword retrieval\u003c\/li\u003e\n\u003cli\u003eScale your infrastructure with disk-based indexing, compression, and async I\/O tuning\u003c\/li\u003e\n\u003cli\u003eSecure sensitive AI data with row-level security, RBAC, and auditing strategies\u003c\/li\u003e\n\u003cli\u003eMonitor performance with real-time metrics like precision@k, recall@k, and embedding drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eUnlike theory-heavy AI books, this guide focuses on \u003cb\u003epractical implementation\u003c\/b\u003e using SQL, PostgreSQL extensions, and real-world architectural patterns. From event-driven pipelines to resilient API handling with asynchronous queues, every concept is grounded in production-ready solutions you can apply immediately.\u003c\/p\u003e\u003cp\u003eWhether you're building intelligent search, autonomous agents, or enterprise-grade AI systems, this book equips you with the tools to \u003cb\u003escale confidently, reduce costs, and maintain full control over your data\u003c\/b\u003e.\u003c\/p\u003e\u003cp\u003eStop duct-taping your AI stack together. Start building smarter-with PostgreSQL at the core.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eGet your copy today and transform your database into a powerful AI engine.\u003c\/b\u003e\u003c\/p\u003e","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":47883350704279,"sku":"9798258982049","price":2802.0,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798258982049.webp?v=1781101339","url":"https:\/\/atlanticbooks.com\/products\/postgresql-18-for-automated-ai-pipelines-automate-embedding-optimize-vector-search-and-scale-your-data-architecture-with-confidence-9798258982049","provider":"Atlantic Books","version":"1.0","type":"link"}