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Category: "Vector Database"

Books

  1. Django 6.1 with Python 3.14
    Django 6.1 with Python 3.14
    From your first project to production: complete web applications with PostgreSQL, semantic search with pgvector, and dynamic interfaces with HTMX
    Franky Bonanno

    Build six complete Django projects, plus a final case study, with the latest Django and Python: PostgreSQL, full-text and semantic search, HTMX, background jobs, multi-tenancy, tests, Docker and deployment. Every result in the book was produced by actually running the code.

  2. Building a Document Management System
    Building a Document Management System
    with Django 6.1, HTMX and pgvector
    Franky Bonanno

    Build a real document management system from scratch to production: OCR, keyword and semantic search, an AI assistant that cites its sources, sharing and approvals, Docker, Nginx and private HTTPS.

  3. PostgreSQL Problem Solver: Advanced SQL Recipes for Ranking, Retention, Funnels, and Vector Similarity
    PostgreSQL Problem Solver: Advanced SQL Recipes for Ranking, Retention, Funnels, and Vector Similarity
    mohammad zeya ahmad

    The problem-first SQL cookbook for analysts. Find your problem, copy the query, get back to work. Tested on PostgreSQL 17.

  4. Mastering Qdrant for RAG Applications
    Mastering Qdrant for RAG Applications
    Building Production Vector Search Systems with the Open-Source Vector Database
    Steve Publications

    Mastering Qdrant for RAG Applications is your practical guide to building production-ready RAG systems with the leading open-source vector database. Learn how to design, optimize, and scale high-performance vector search using Qdrant through clear explanations, real-world examples, and hands-on code.