TerminusDB creates a vector database to leverage vector embeddings for tasks such as full-text search, entity resolution, similarity search, and clustering.
The database uses OpenAI's embeddings and an HNSW graph for indexing vector spaces, providing semantic similarity for semantically close inputs.