FAISS vs. OpenSearch
Compare FAISS vs. OpenSearch by the following set of capabilities. We want you to choose the best database for you, even if it’s not us.
FAISS vs. OpenSearch on Scalability
No. Can not scale beyond single node.
Yes.
No distributed data replacement
Both
FAISS scalability
Without any distributed data replacement, FAISS is not able to scale beyond a single node
OpenSearch
OpenSearch supports horizontal scaling, cluster management optimizations, and efficient shard allocation, making it suitable for handling large datasets and high query loads effectively.
FAISS vs. OpenSearch 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, vector search & keyword search & scalar filtered search
FLAT, IVS_FLAT, IVF_SQ8, IVF_PQ, HNSW, BIN_FLAT and BIN_IVF_FLAT
ANN
FAISS functionality
FAISS is an algorithm to support kNN search.
OpenSearch
OpenSearch supports:
- Vectors with up to 16,000 dimensions.
- Vector generation through external libraries or directly within OpenSearch.
- Both binary and dense vectors.
- Cosine Similarity, Inner Product, and L2 Distance (Euclidean).
- Integration with multiple engines, including NMSLIB, Faiss, and Lucene, to facilitate vector indexing and searching.
FAISS vs. OpenSearch 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
No. Vector search is an add-on to OpenSearch.
Python, JavaScript
Java, Python, JavaScript, Go, and .Net
FAISS vs. OpenSearch: 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
OpenSearch
OpenSearch is an open-source software suite for search, analytics, security monitoring, and observability applications. It is not purpose-built for vector storage and search workloads but introduces a vector search plugin to provide this capability. Amazon OpenSearch Service is an AWS-managed service for OpenSearch.
Apache 2.0