FAISS vs. MongoDB Atlas
Compare FAISS vs. MongoDB Atlas by the following set of capabilities. We want you to choose the best database for you, even if it’s not us.
FAISS vs. MongoDB Atlas on Scalability
Yes. Atlas introduced search nodes, providing dedicated infrastructure for Atlas search and vector search workloads.
No. Can not scale beyond single node.
No distributed data replacement
Yes. Atlas can dynamically balance the data between shards via range migrations.
FAISS scalability
Without any distributed data replacement, FAISS is not able to scale beyond a single node
FAISS vs. MongoDB Atlas 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 - Pre-filtering using an MQL match experssion that compares an indexed field with boolean, number, or string.
No. MongoDB organizes data into databases and collections, but it does not have a hierarchical structure like sub-collections within collections.
FLAT, IVS_FLAT, IVF_SQ8, IVF_PQ, HNSW, BIN_FLAT and BIN_IVF_FLAT
HNSW
FAISS functionality
FAISS is an algorithm to support kNN search.
MongoDB (Atlas Vector Search)
Atlas has support for vector embeddings that are less than or equal to 2048 dimensions.
FAISS vs. MongoDB Atlas 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
Add on to Atlas
Python, JavaScript
C#, Java, Node, Pymango
FAISS vs. MongoDB Atlas: what’s right for me?
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
MongoDB (Atlas Vector Search)
Altas is a managed cloud database based on MongoDB document database.
SaaS
The Definitive Guide to Choosing a Vector Database
Overwhelmed by all the options? Learn key features to look for & how to evaluate with your own data. Choose with confidence.