pagefind VS vespa

Pagefind is a static search library that aims to perform well on small or large sites, while using as little bandwidth as possible, and you don't have to host any infrastructure.

In theory, if we ran lower level code, we would be using less resources. That's more than a theory. Go to this video where I demonstrate Pagefind, written in Rust and compiled to Wasm as target, as a static app that ingests and indexes HTML documents and runs super efficient search queries, all client-side.

✅ Pagefind static search library integration

I use Astro SSG and Cloudflare Pages. I use https://github.com/cloudcannon/pagefind for search on my Astro setup. You can test the search functionality here https://tinyrocket.pages.dev/.

From its repo: "Pagefind runs after any static site generator and automatically indexes the built static files. Pagefind then outputs a static search bundle to your website, and exposes a JavaScript search API that can be used anywhere on your site."

Pagefind is cool!

An option there is https://pagefind.app/ — not as fast as a persistent server but solves some of the deployment and bandwidth issues.

Vespa(4.3k ⭐) → A fully featured search engine and vector database. It supports vector search (ANN), lexical search, and search in structured data, all in the same query. Integrated machine-learned model inference allows you to apply AI to make sense of your data in real time.

If ES doesn't work for you, I recommend Vespa. https://github.com/vespa-engine/vespa

Others have made other suggestions, but Vespa has two unique features. First it is battle tested at a large scale, second it supports combining the keyword and vector scores in several ways. The latter is something that other hybrid systems don't do very well in my experience including ES/Solr.

After looking at various alternatives, I'm thinking of trying out https://vespa.ai/ [0]

[0] https://github.com/vespa-engine/vespa