Luckily there are faster and smaller alternatives in Rust for the ElasticSearch - Toshi[1], Meili[2] and Sonic[3]. In the age of Rust there is no need to use JVMs overhead.
[1] https://github.com/toshi-search/Toshi
[1] https://github.com/toshi-search/Toshi
One thing to point out though is that Typesense, MeiliSearch (and Algolia) are designed for Instant Search experiences, and so hold the entire index in memory. So for petabyte scale data (like logs) it might be wasteful (and expensive) to store that size of data in memory. This is where ElasticSearch shines and of course comes with it the overhead of managing it.
This is actually very interesting project. Do we have some benchmark that sonic works on huge scale with lot of data?
they also claim
> It is used to index half a billion objects on a $5/mth 1-vCPU SSD cloud server (as of 2019)
> Sonic is integrated in all Crisp search products on the Crisp platform. It is used to index half a billion objects on a $5/mth 1-vCPU SSD cloud server (as of 2019). Crisp users use it to search in their messages, conversations, contacts, helpdesk articles and more.
Of all the projects you mention however, only Toshi addresses clustering, and as an experimental feature.
If you're using it for logfiles, the only real alternative I know is Grafana's loki.
Too bad we're talking about software license here.
Rust and C and manual memory management have overhead too.