What is Chroma?
Chroma (also known as ChromaDB) is an open-source embedding database designed specifically for AI applications that need to store, search, and retrieve vector embeddings efficiently. It provides a simple, developer-friendly interface for managing collections of embeddings along with their associated metadata and documents, making it easy to build retrieval-augmented generation (RAG) systems and agent memory architectures.
The database handles the complexities of vector storage and similarity search behind a straightforward API, allowing developers to focus on their application logic rather than the intricacies of vector indexing and retrieval. Chroma supports various distance metrics for similarity search, metadata filtering to narrow down results, and integration with popular embedding models. It can run in-memory for development and testing or persist data to disk for production use.
Chroma has gained popularity in the AI development community due to its ease of use and good integration with frameworks like LangChain and LlamaIndex. Its open-source nature and ability to run locally make it an attractive choice for developers building prototype AI applications, while its straightforward scaling path supports production deployments. The project emphasizes developer experience, with features like automatic embedding generation and simple query interfaces.