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Using ChromaDB with Python: Build a Lightweight Local Vector Database for AI Applications

By IT From Zero October 2, 2026

Suffering from OOM killer memory crashes due to in-memory NumPy vectors? Here is how to integrate ChromaDB PersistentClient in Python for a lightweight, robust local vector database.

MySQL

MySQL 9.0 and VECTOR: Embedding Storage Solution for AI Apps Without a Secondary DB

By IT From Zero July 22, 2026

MySQL 9.0 officially supports the VECTOR data type. Learn how to store AI embeddings, calculate Cosine distance, and build efficient semantic search systems directly in MySQL.

Database

Setting Up Milvus Vector Database with Docker: Building a Knowledge Store for RAG and AI

By IT From Zero June 18, 2026

A guide to installing Milvus Vector Database with Docker Compose, creating collections, storing vector embeddings, and building a complete RAG pipeline. Includes tips on choosing index types, chunking strategies, and production optimization from real-world experience.

Database

Getting Started with ChromaDB: The Open-Source Vector Database for Building AI Agent Knowledge Systems

By IT From Zero June 13, 2026

ChromaDB is an open-source vector database for semantic storage and search — lightweight enough to run locally, powerful enough to serve as the foundation for RAG systems and AI Agents. This guide walks through installation, document indexing, semantic search queries, and Docker deployment with practical, step-by-step examples.

Database

pgvector Guide: Storing and Searching Vector Embeddings in PostgreSQL for AI and RAG Applications

By IT From Zero April 22, 2026

pgvector is a PostgreSQL extension that lets you store and search vector embeddings directly in your existing database — no need to deploy a separate system. This guide covers installation, HNSW index creation, semantic search, and integrating pgvector into a Python RAG pipeline, with practical monitoring tips from real-world experience.

Building Semantic Search with Python: When Computers Truly ‘Understand’ User Intent

By IT From Zero April 7, 2026

The era of dry keyword search is over. Learn to build a smart Semantic Search system with Python, helping computers understand the meaning of queries and return accurate results even without matching keywords.