minisearch VS orama

I wrote an online catalog a while back (and I need to get back on adding graphics and products at some point). It’s written using Eleventy and the minisearch library. The source and data are available on Github if you want to see how I did things. I’m not a professional web designer either, but it was a fun project.

You could have a look at https://github.com/lucaong/minisearch/

If you're dealing with thousands of records or less, searching titles and summaries rather than long bodies of text, I recommend looking into client-side solutions. Nothing beats the responsiveness of search-as-you-type entirely on the client side. It can be fairly sophisticated fulltext search. For example, I've built had great success with MiniSearch.

I quite enjoy minisearch[1] which is also 0 dependencies, actively maintained, and I expect would work well in a worker environment. I dropped it into a service worker and plugged it with a simple point in polygon script to enable geosearch for a recent project[2] and it played v. nicely.

[1] https://github.com/lucaong/minisearch

No magic here, the underlying engine is Minisearch, which uses the BM25 algorithm (the de facto standard among search libraries). Omnisearch adds a magic sauce during indexing by converting notes into custom objects, with the following fields: - body (the plain markdown text) - filename & yaml aliases - level 1 headers - level 2 headers - level 3 headers

It's actually really simple! Minisearch did most of the heavy lifting so all we needed to do was the crawling, storing and UI etc. I'd check that out if you're interested in the search part!

We use MiniSearch for searching, while fast-fuzzy is used for highlighting of detected search terms.

Let's break into the steps to utilize Orama and analyze how it works. I won't dig into the technical stuff because, hey, it's an open-source project, which means you can easily peek at the source code, no problemo!

If you are interested in it, you can learn more about it in the official documentation. And don't forget to follow Orama on Twitter and Michere Riva its CTO.

I'll use the Lyra repository for this article, so thanks to the Lyra contributors if this article has a great git history and awesome code.

You can checkout lyra, its in-memory full text search engine for javascript