Free Lesson

Build a vector database from scratch (part two)

60 min

May 14, 2025 12:00 PM

Virtual (Zoom)

In this video

What you'll learn

Learn how embedding similarity search works

Learn the most common graph-based vector search algorithm used in Elasticsearch, Weaviate, QDrant, Pinecone, etc

See where vector search goes wrong

As you watch an expert live-code, see where the algorithm falls apart as a real-life expert makes a mistake

Deepen your vector search knowledge

Dense vectors provide specific constraints on retrieval solutions - learn what these are, how they can go wrong

Why this topic matters

RAG systems all use vector databases. HNSW (Hierarchical Navigable Small Worlds) is the most common algorithm. If you want to build RAG, you should appreciate how this algorithm works (Missed part 1? Catch up here https://maven.com/p/866f13/doug-live-codes-a-vector-database)

You'll learn from

Doug Turnbull

Led Search at Shopify, Reddit

Eric Pugh

Cofounder OpenSource Connections

Previously at

See all products from Doug