| I've been experimenting with SQLite FTS as a way of adding search to an otherwise static site. The big advantage of SQLite FTS is that it's really cheap to run. The index is a single static file on disk, then you add a Python process (I'm using https://github.com/simonw/datasette ) to run queries against it. Much less resource intensive than running Solr or Elasticsearch. It also works surprisingly well - I've run FTS queries against tables that are up to around 10GB on disk and performance is great. It's no way near as featureful as Lucene, but for small to medium sized projects it's easily good enough. As for deployment: if the SQLite .db index file is small enough you can bundle it up as part of a static deployment, e.g. bundled in a Docker container. I've done this using Heroku, Google Cloud Run, https://fly.io/ and Zeit Now (aka Vercel). If the content lives in a git repository you can hook up CI (or a GitHub Action) to build and publish a new copy of the SQLite index on every change. I've started thinking of this pattern as a kind of static-dynamic site: there's dynamic server-side code but it's running in read-only containers, so you can scale it up by running more copies and if anything goes wrong you just restart the container. https://til.simonwillison.net/ is my most recent site to use this pattern, see https://github.com/simonw/til for how it works. I also wrote this tutorial describing the pattern a while ago: https://24ways.org/2018/fast-autocomplete-search-for-your-we... |