benchmark comparison
altor-vec vs Pinecone
Managed vector database versus browser-native retrieval.
This comparison is intentionally not framed as a universal winner. Pinecone is infrastructure. altor-vec is a client-side search primitive. The decision starts with where the corpus should live and who should pay the latency cost.
Comparison table
| Category | altor-vec | Pinecone |
|---|---|---|
| Runtime model | Browser WebAssembly HNSW running entirely on the client. | Managed vector database accessed over an API. |
| Bundle size / delivery | ~54KB gzipped library payload plus your vector asset. | No client search bundle, but every query depends on a backend call. |
| Query latency | ~0.6ms p95 local ANN lookup on a 10K / 384d benchmark excluding embedding generation. | Usually tens of milliseconds plus network roundtrip, which is acceptable for backend retrieval but not as snappy for keystroke UX. |
| Memory usage | Browser memory scales with the shipped corpus; roughly ~17MB for a 10K / 384d representative index. | Server-side memory and storage, with almost nothing held in the browser. |
| Features | Approximate nearest-neighbor search, serialization, local-first delivery, no hosted ops. | Metadata filtering, namespaces, scaling, backups, observability, and hosted operations. |
| Dataset sweet spot | Best for moderate corpora that are safe to ship to the user. | Best for large, private, multi-tenant, or frequently updated corpora. |
Where altor-vec wins
- Instant local UX without an API dependency.
- Zero per-query infrastructure cost after shipping the asset.
- Good fit for offline or privacy-sensitive search experiences.
Where Pinecone wins
- Large private datasets and frequent writes.
- Operational controls, filtering, and hosted scaling.
- Clearer fit for multi-user backend retrieval and production RAG infrastructure.
Honest decision guide
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.
The honest pattern across all of these benchmark pages is simple: if the search corpus should stay on the server, choose server-oriented infrastructure. If the search corpus is intentionally shipped with the product and the UX benefit of local retrieval matters more than backend scale, altor-vec is usually the more natural fit.
FAQ
Is altor-vec a Pinecone replacement?
Not broadly. They solve different layers of the stack. altor-vec handles local retrieval; Pinecone handles hosted vector infrastructure.
When does Pinecone clearly win?
When the corpus is large, private, access-controlled, or updated continuously.
When does altor-vec clearly win?
When the search experience itself belongs in the browser and local latency matters more than backend scale.
Get started: npm install altor-vec · GitHub