We will experiment with two databases
Chroma is the open-source embedding database. Chroma makes it easy to build LLM apps by making knowledge, facts, and skills pluggable for LLMs. Chroma gives you the tools to:
- store embeddings and their metadata
- embed documents and queries
- search embeddings
Chroma prioritizes:
- simplicity and developer productivity
- analysis on top of search
- it also happens to be very quick
Qdrant is powering the next generation of AI applications with advanced and high-performant vector similarity search technology.
Qdrant is a vector database & vector similarity search engine. It deploys as an API service providing search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more!
- Easy to Use API. Provides the OpenAPI v3 specification to generate a client library in almost any programming language. Alternatively utilize ready-made client for Python or other programming languages with additional functionality.
- Fast and Accurate. Implement a unique custom modification of the HNSW algorithm for Approximate Nearest Neighbor Search. Search with a State-of-the-Art speed and apply search filters without compromising on results.
- Filtrable. Support additional payload associated with vectors. Not only stores payload but also allows filter results based on payload values. Unlike Elasticsearch post-filtering, Qdrant guarantees all relevant vectors are retrieved.