Chroma serves as a vector database designed for storing and retrieving embeddings—mathematical representations of data used for tasks like semantic search or similarity search. Embeddings transform items like text or images into vectors in a multi-dimensional space, allowing machines to evaluate how similar or different these items are. Chroma efficiently indexes and handles these vectors, facilitating quick queries and retrievals, akin to libraries like Faiss or Annoy.