Vector Database Fundamentals for Developers: Core concepts to integrate vector search into software solutions

By Laitan Michael

Master the Core Concepts and Tools Behind Vector Databases and AI Retrieval Systems

In a rapidly evolving AI landscape, knowing how to store, search, and retrieve vector embeddings is no longer optional. Whether you're building RAG pipelines, designing search infrastructure, or integrating with modern LLM frameworks, this book gives you a clear and practical understanding of vector databases from the ground up.

Many developers struggle to implement scalable vector search because most resources are either too academic or too shallow. This book bridges that gap. It walks you through the mathematical foundations, shows you how real systems are built, and gives you the tools to reason about tradeoffs across performance, cost, and design.

What You Will Learn: Key concepts: cosine similarity, vector norms, top-k retrievalWhen and how to use FAISS, Milvus, Weaviate, and PineconeUnderstanding indexes like IVF, HNSW, PQ, DiskANNHow RAG systems work and how retrieval affects output qualityEvaluating embeddings and retrievers with MRR, NDCG, RecallMultilingual search, memory systems, and semantic filtersSecurity, tenancy, real-time updates, and production scalingEnd-to-end design of indexing pipelines and RAG workflows
Includes Practical Add-Ons: Cheat Sheet for quick referenceFlashcards to test your understandingKey Takeaways and Application TipsCommon Mistakes to avoidFull Index for quick lookups
Includes Code and Math Equations:
This is a hands-on technical book. You'll find working code in Python, SQL, and Bash, along with clearly formatted mathematical equations that explain scoring functions, distances, and evaluation metrics. Every concept is grounded in practical logic and tied to real-world use.

Grab your copy today and build your foundation in modern vector search and AI retrieval.

• Format: Paperback
• Language: English
• ISBN: B0FSXXR5Z5
• ISBN13: 9798267302449
• Release Date: September 2025
• Publisher: Independently Published
• Length: 208 Pages
• Weight: 0.81 lbs.
• Dimensions: 0.4" x 7.0" x 10.0"