Chroma DBMS

Context:
- It can (typically) handle vector embeddings which are crucial for machine learning applications.
- It can (often) integrate seamlessly with other tools such as LangChain, LlamaIndex, and OpenAI, facilitating the development of large language models.
- It can range from being used in small-scale projects to being an essential component in large-scale AI deployments.
- It can leverage its open-source nature to encourage collaboration and innovation within the community.
- It can be utilized in various environments, thanks to its compatibility with multiple programming languages and frameworks.
- ...
Example(s):
- Version 1.0 (2021) that introduced basic vector storage capabilities.
- Version 2.3 (2023) that enhanced querying features and integration with external AI services.
- ...
Counter-Example(s):
- Pinecone DBMS.
See: Color Science, Image Processing Software, Data Storage Solutions.

References

https://docs.trychroma.com/
- QUOTE: Chroma is the open-source embedding database. Chroma makes it easy to build LLM apps by making knowledge, facts, and skills pluggable for LLMs.