Weaviate Vector Search Engine – Introduction
summary
Weaviate is a cloud-native open source vector search engine that stores objects as vectors, uses built-in and pluggable ML models for text and images, and returns semantic nearest-neighbor results instead of keyword matches. Live demo searches over 10,000 reviews show retrieval by concept (wine that fits fish) and automatic classification. Exposes GraphQL API plus REST and Python/Go/JavaScript clients, supports transformer and image modules, and falls back to neighbor search when no model is used. Indexing is real-time and graph-like relations are materialized.
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chapters (9)
- 0:00Introduction to Weaviate
- 4:50What is a vector search engine
- 8:01How Weaviate works
- 10:29Semantic search with Weaviate
- 15:30Traditional vs vector search
- 17:35Custom models and use cases
- 19:54Enterprise applications
- 21:45Getting started with Weaviate
- 22:37Q&A and closing
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