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Module 4 - Vector Databases

Overview​

Vector databases are specialized systems designed for storing and searching high-dimensional vectors. This module covers the major vector database options, their features, and how to choose the right one for your RAG system.

Learning Objectives​

  • Understand what makes vector databases different
  • Learn about indexing algorithms (HNSW, IVF)
  • Compare Pinecone, Weaviate, Chroma, Milvus, Qdrant
  • Implement vector stores with LangChain

Module Content​

1. Introduction to Vector Stores​

  • What makes them different from traditional databases
  • Indexing algorithms (HNSW, IVF, Flat)
  • Metadata storage and filtering

2. Pinecone, Weaviate, Chroma​

  • Hosted vs self-hosted options
  • Pricing and features comparison
  • Setup and usage guides

3. Milvus, Qdrant, and Others​

  • Open source options
  • PostgreSQL + pgvector
  • FAISS and Redis Vector Search
  1. Vector Stores Intro - Fundamentals
  2. Popular Options - Pinecone, Weaviate, Chroma
  3. Open Source - Milvus, Qdrant, pgvector
  4. Quiz - Module 4 - 30 questions

Choose the right database for your vectors!