What is a Vector Database? Explained Simply with Real-World Examples

Описание: Curious how modern AI apps find meaning in images, text, or video? Enter the vector database. In this explainer, Brian Sam-Bodden breaks down what vector databases are, why they’re essential for unstructured data, and how techniques like cosine similarity, HNSW indexing, and vectorization power smarter search and recommendations.

Chapters
0:00 Introduction
0:40 From relational to unstructured data
2:30 Why structured data isn’t enough
4:20 What is a vector?
6:00 How ML models vectorize data
7:30 Indexing and searching vectors
9:50 Flat vs HNSW indexing
12:00 What makes a real vector DB
14:00 Real-world use cases and closing

Topics covered:
Unstructured vs structured data
Vector embeddings
Cosine similarity
ANN and HNSW indexing
How search, recs, and AI pipelines use vector DBs

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Resources & links
Docs: https://redis.io/docs
Try it out: https://redis.com/try-free


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