I really hope this is the long awaited thing. From the number of commits, this project looks huge, Elasticsearch is really a big liability for resource limited deployments, I have seen some smaller projects made in Rust and Go but can't compete with Elasticseatch at any level, but this looks different and I hope it does.
Xapiand: A fast, simple, modern search and storage engine
21–30 of 68 posts
Re: Xapiand: A fast, simple, modern search and storage engine
#22Haven't heard of Vespa? https://vespa.ai
Re: Xapiand: A fast, simple, modern search and storage engine
#23Re: Xapiand: A fast, simple, modern search and storage engine
#24I'm interested, can anyone give a quick overview of why you'd use this over Elasticsearch?
Well for one, Java is ridiculously memory hungry. The resource costs of Elasticsearch is the #1 reason I'm not using it. I've seen a few projects which had the aim of reimplementing the Elasticsearch backend in Rust, but were incomplete. That would be my ideal solution, personally.
OpenJ9 is a low memory footprint jvm
Re: Xapiand: A fast, simple, modern search and storage engine
#25Re: Xapiand: A fast, simple, modern search and storage engine
#26Earlier quoted context omitted.
I don't know how true that is anymore, that "Java is ridiculously memory hungry". It does power billions of devices, after all. :-P
why do you think they called their product "elastic"? java heap size? 32gb? above that and you are in for problems
which problem? There is no problem, especially since the latest gc. Only tradeof
Re: Xapiand: A fast, simple, modern search and storage engine
#27I was genuinely wondering recently why the Hackernews site search tool didn't show a very recent article with very obvious keywords, that google, for example, had in the first place in the results, when adding "Hn" to those 2 keywords in the search field. Is it a matter of the indexing, it means the article was too recent and it wasn't yet in the Algolia's(I believe) based HN's search tool memory; and in this case go…
Google search with site:news.ycombinator.com (and optionally a time limit, which I wish wasn't limited to past hour/day/week/month/year) seems consistently superior to what Algolia provides.
Algolia is YC company, so I assume that's the main reason it's being used. But that it does such an awful job with such a simply structured site isn't compelling.
Re: Xapiand: A fast, simple, modern search and storage engine
#28I'm interested, can anyone give a quick overview of why you'd use this over Elasticsearch?
Well for one, Java is ridiculously memory hungry. The resource costs of Elasticsearch is the #1 reason I'm not using it. I've seen a few projects which had the aim of reimplementing the Elasticsearch backend in Rust, but were incomplete. That would be my ideal solution, personally.
Yes, exactly the same for me, I've tried all the configuration possible with the jvm (that I know of) but nothing really worked to make it use a more reasonable amount of memory.
Re: Xapiand: A fast, simple, modern search and storage engine
#29Somewhat unrelated but I've written a restful search server that's powered by Sqlite's full-text search. Extremely lightweight python (flask) app. Nice for blogs or small projects, if I say so myself!
Re: Xapiand: A fast, simple, modern search and storage engine
#30I was genuinely wondering recently why the Hackernews site search tool didn't show a very recent article with very obvious keywords, that google, for example, had in the first place in the results, when adding "Hn" to those 2 keywords in the search field. Is it a matter of the indexing, it means the article was too recent and it wasn't yet in the Algolia's(I believe) based HN's search tool memory; and in this case go…
https://hn.algolia.com/ only searches the text content of the submitted stories (as in the title and url) and the comments.
It doesn't index the actual article content nor take into account links across sites and content like Google does. Algolia (as self-described) is designed to search for things (like products in a ecommerce store) rather than text with concepts, relations, and entities in a knowledge graph like Google.