Chroma vs. FAISS
Compare Chroma vs. FAISS by the following set of capabilities. We want you to choose the best database for you, even if it’s not us.
Chroma vs. FAISS on Scalability
No. Can not scale beyond single node.
No. Can not scale beyond single node.
No distributed data replacement
No distributed data replacement
Chroma scalability
Without any distributed data replacement, Chroma is not able to scale beyond a single node
FAISS scalability
Without any distributed data replacement, FAISS is not able to scale beyond a single node
Chroma vs. FAISS on Functionality
Performance is the biggest challenge with vector databases as the number of unstructured data elements stored in a vector database grows into hundreds of millions or billions, and horizontal scaling across multiple nodes becomes paramount.
Yes with scalar filtering
1 (HNSW)
FLAT, IVS_FLAT, IVF_SQ8, IVF_PQ, HNSW, BIN_FLAT and BIN_IVF_FLAT
Chroma functionality
Chroma uses HNSW algorithm to support kNN search.
FAISS functionality
FAISS is an algorithm to support kNN search.
Chroma vs. FAISS on Purpose-built
What’s your vector database for?
A vector database is a fully managed solution for storing, indexing, and searching across a massive dataset of unstructured data that leverages the power of embeddings from machine learning models. A vector database should have the following features:
- Scalability and tunability
- Multi-tenancy and data isolation
- A complete suite of APIs
- An intuitive user interface/administrative console
Python, JavaScript
Python, JavaScript
Chroma vs. FAISS: what’s right for me?
Chroma
Chroma is maintained by a single commercial company offering a non-scalable single node. License: Apache-2.0 license
FAISS
Faiss is a powerful library for efficient similarity search and clustering of dense vectors, with GPU-accelerated algorithms and Python wrappers, developed at FAIR, the fundamental AI research team at Meta License: MIT license