Moss
Search runtime that loads cloud-built indexes into your app process for local retrieval.
Moss is a search runtime that loads an index built in Moss Cloud into the application process, so queries run locally without a network hop. It offers hybrid semantic and keyword retrieval, built-in embeddings, metadata filtering and a WebAssembly build for the browser, with SDKs for Python, TypeScript, Elixir and C. Every process that loads an index holds its own in-memory copy, so memory sizing matters. A free tier is available, with paid plans from $30/month plus usage.
Pricing: Usage-based
Choosing a vector database right now?
One click, anonymous. Helps us know our visitors.
Thanks, that helps.
Choosing a vector database right now?
One click, anonymous. Helps us know our visitors.
Thanks, that helps.
Moss Alternatives
Explore 27 products in the Vector databases category. View all Moss alternatives.
FAISS
Meta's open-source library for efficient similarity search and dense vector clustering
Turbopuffer
Serverless vector and full-text search engine built on object storage for cost-efficient scale
Marqo
Use your data to increase relevance with vector search.
Chroma
The AI-native open-source embedding database
pgvecto.rs
pgvecto.rs is a Postgres extension that provides vector similarity search functions.
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