benchmarks

altor-vec benchmark comparisons

These pages compare altor-vec with hosted vector databases, embedded engines, and browser-capable alternatives. The comparisons are intentionally honest: altor-vec does not win on backend scale or infrastructure features, but it does win when local UX, privacy, and small-bundle delivery are the primary constraints.

Browse all 10 benchmark pages

Pinecone

Managed vector database versus browser-native retrieval.

Weaviate

Feature-rich vector database versus lightweight client-side HNSW.

hnswlib-wasm

Two browser-capable HNSW options with different packaging tradeoffs.

USearch

Portable ANN engine versus an aggressively small browser-focused package.

Voyager

Browser-first vector search alternatives with different algorithm and packaging tradeoffs.

FAISS WASM

Research-grade ANN lineage versus a small production-friendly browser package.

ChromaDB

Application database for embeddings versus static browser retrieval.

Lance

Columnar/vector data platform tradeoffs versus browser-native ANN.

Milvus Lite

Embedded/server vector database tradeoffs versus fully in-browser retrieval.

Server-Side Vector Search

When local browser retrieval wins and when server-side retrieval clearly wins.

Summary table

Comparison	What is being compared	Short takeaway
Pinecone	Managed vector database versus browser-native retrieval.	Choose Pinecone when search is part of your backend platform. Choose altor-vec when search is a frontend capability and the corpus is intentionally shipped to the browser.
Weaviate	Feature-rich vector database versus lightweight client-side HNSW.	Weaviate wins on backend capability and scale. altor-vec wins when you want vector retrieval to behave like a frontend dependency, not a service to operate.
hnswlib-wasm	Two browser-capable HNSW options with different packaging tradeoffs.	If both reach your recall target, frontend ergonomics and payload size become the real decision factors. Benchmark with your own vectors before claiming a winner.
USearch	Portable ANN engine versus an aggressively small browser-focused package.	USearch is broader. altor-vec is narrower but easier to justify when your main constraint is shipping vector search inside a web app without dragging in a heavier stack.
Voyager	Browser-first vector search alternatives with different algorithm and packaging tradeoffs.	At this tier, benchmark on your own corpus. Developer experience, bundle budget, and how predictable the results feel in the browser often decide more than theory alone.
FAISS WASM	Research-grade ANN lineage versus a small production-friendly browser package.	FAISS wins on breadth and lineage. altor-vec wins on browser pragmatism and small-package delivery.
ChromaDB	Application database for embeddings versus static browser retrieval.	ChromaDB is stronger as an application data layer. altor-vec is stronger as a browser-delivered retrieval primitive.
Lance	Columnar/vector data platform tradeoffs versus browser-native ANN.	Lance is more compelling when you are building a vector-aware data stack. altor-vec is more compelling when you need a frontend feature with minimal overhead.
Milvus Lite	Embedded/server vector database tradeoffs versus fully in-browser retrieval.	Milvus Lite is closer to embedded database infrastructure. altor-vec is closer to a frontend dependency. The right choice depends on which role you actually need.
Server-Side Vector Search	When local browser retrieval wins and when server-side retrieval clearly wins.	Browser search wins when retrieval is part of the interface itself. Server search wins when retrieval is part of the infrastructure. Most teams should choose based on that boundary first, not on raw ANN marketing claims.