{"product_id":"vector-database-development-for-developers-designing-building-and-scaling-high-performance-embedding-systems-for-applications-9798250588270","title":"Vector Database Development For Developers: Designing, Building, and Scaling High Performance Embedding Systems for Applications","description":"\u003cp\u003e • Author(s): Zhao Colton\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Data Science - Data Warehousing\u003c\/p\u003e\u003cp\u003eArtificial intelligence applications increasingly rely on semantic search, recommendation systems, retrieval-augmented generation (RAG), and similarity matching. At the center of these systems lies a new category of infrastructure: vector databases.\u003cbr\u003e\u003ci\u003eVector Database Development\u003c\/i\u003e provides a structured, engineering-focused guide to designing and implementing embedding-driven data systems for modern AI applications. This book moves beyond surface-level introductions and explores how vector indexing, similarity search algorithms, and distributed storage architectures operate in production environments.\u003cbr\u003eInside this book, you will learn: \u003c\/p\u003e\u003col\u003e\n\u003cli\u003eThe mathematical and architectural foundations of vector embeddings\u003c\/li\u003e\n\u003cli\u003eIndexing strategies such as HNSW, IVF, and approximate nearest neighbor search\u003c\/li\u003e\n\u003cli\u003eStorage design and memory optimization techniques\u003c\/li\u003e\n\u003cli\u003eIntegrating vector databases with AI pipelines and LLM workflows\u003c\/li\u003e\n\u003cli\u003eDesigning retrieval-augmented generation systems\u003c\/li\u003e\n\u003cli\u003ePerformance benchmarking and tuning methods\u003c\/li\u003e\n\u003cli\u003eDeployment strategies for scalable infrastructure\u003c\/li\u003e\n\u003c\/ol\u003eThe book provides practical implementation patterns using real-world design principles. It also discusses system trade-offs, data modeling decisions, and security considerations relevant to enterprise deployments.\u003cbr\u003eThis guide is suitable for backend engineers, machine learning engineers, AI developers, and architects who want to understand how vector databases function internally and how to build reliable, scalable solutions around them.\u003cbr\u003eRather than offering quick tutorials, this book presents a long-term engineering perspective on embedding-based data systems.","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":47568431939735,"sku":"9798250588270","price":1816.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798250588270.webp?v=1774868269","url":"https:\/\/atlanticbooks.com\/products\/vector-database-development-for-developers-designing-building-and-scaling-high-performance-embedding-systems-for-applications-9798250588270","provider":"Atlantic Books","version":"1.0","type":"link"}