quickwit

Nice... it's cool to see how different companies are putting together best fit solutions. I'm also glad that they at least started out with off the shelf apps instead of jumping to something like a bespoke solution early on. Quickwit[1] looks interesting, found via Tantivity reference. Kind of like ES w/ Lucene. 1. https://github.com/quickwit-oss/quickwit

"What are your main use cases for search or log indexing?" To me, storing and searching logs is quite different from most other search use-cases, and it's not obvious that they should be handled by the same piece of software. For example, tokenization, stemming, language support many other things and are basically useless in log search. Also, log search is often storing a lot of data, and rarely retrieving it (different usage pattern from many search use-cases which tend to be less write-heavy and more about reads). I know ElasticSearch has had success in both, but if I were Manticore/Typesense/Meilisearch I'd probably just skip logs altogether. Loki, QuickWit and other such tools are likely better suited for logs. - https://github.com/quickwit-oss/quickwit - https://github.com/grafana/loki

Meilisearch is great, used it for a quick demo However if you need a full-text search similar to Apache Lucene, my go-to options are based on Tantivy Tantivy https://github.com/quickwit-oss/tantivy Asian language, BM25 scoring, Natural query language, JSON fields indexing support are all must-have features for me Quickwit - https://github.com/quickwit-oss/quickwit - https://quickwit.io/docs/get-started/quickstart ParadeDB - https://github.com/paradedb/paradedb I'm still looking for a systematic approach to make a hybrid search (combined full-text with embedding vectors). Any thoughts on up-to-date hybrid search experience are greatly appreciated