Sep 08, 2023
Using Supabase’s vector database with PostgreSQL
Original View
- Understanding vectors: Vectors are containers holding an ordered set of numbers. Embeddings are a type of vector that represent complex data in a lower-dimensional space.
- Use cases of embeddings: Embeddings can be used for search, clustering, recommendations, anomaly detection, diversity measurement, and classification.
- Enabling vectors in Supabase: Supabase is a PostgreSQL extension that allows storing and querying vector embeddings directly in the database.
- Creating embeddings with OpenAI: OpenAI can be used to generate embeddings for text data.
- Implementing search functionality: Similarity between embeddings can be computed using vector mathematical operations, such as cosine distance, to implement search functionality.