Introduction to Vector Databases
Explore the purpose and architecture of vector databases, designed for efficient storage and retrieval of high-dimensional vectors.
What are Vector Databases?
Welcome to the world of vector databases! These are specialized databases designed to store, index, and query high-dimensional vectors efficiently.
Think of them as super-powered filing cabinets for the numerical representations of your data, making them crucial for modern AI applications like Retrieval Augmented Generation (RAG).
Why Traditional DBs Fall Short
Traditional databases (like SQL or NoSQL) are excellent for structured data, exact matches, and keyword searches.
However, they struggle when you want to find items based on their semantic similarity or 'meaning'. They can't easily tell you which documents are 'conceptually similar' to your query.
All lessons in this course
- Understanding Text Embeddings
- Introduction to Vector Databases
- Storing and Retrieving Embeddings
- Measuring Embedding Similarity