benchmark comparison

altor-vec vs Lance

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

Lance is not just an ANN library; it sits closer to a data format and platform story. That makes it powerful for data-heavy workflows, but it also means it is solving a broader problem than a tiny browser vector dependency.

These numbers are representative, not universal. Bundle size, query latency, and memory usage all vary with vector dimensions, index parameters, browser runtime, hardware, and whether embeddings are generated on device or ahead of time.

Comparison table

Categoryaltor-vecLance
Runtime modelIn-browser ANN runtime for shipped apps.Vector-aware data platform and file-format ecosystem used in data and backend workflows.
Bundle size / delivery~54KB gzipped library payload.Broader integration footprint because the value proposition goes beyond a tiny browser bundle.
Query latencyInteractive local lookup in the browser.Good performance in data-platform contexts, but not optimized around the same frontend-delivery constraint.
Memory usageBrowser memory is the main limit.Designed for larger data workflows where storage and access patterns differ from a shipped web asset.
FeaturesFocused ANN search and serialization.Broader table, storage, and vector ecosystem capabilities.
Dataset sweet spotCurated corpora bundled into web apps.Teams working with larger vector datasets and data-engineering style workflows.

Where altor-vec wins

Where Lance wins

Honest decision guide

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.

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 Lance overkill for browser-only search?

It can be, depending on your needs. If you just want a small client-side ANN layer, a narrow library is often easier to justify.

When does Lance make more sense?

When vectors are part of a broader data storage and pipeline story rather than just a frontend capability.

What is altor-vec's advantage here?

Low-friction delivery for app-embedded search.

Get started: npm install altor-vec · GitHub