I ran a YaCy instance for a while like a decade ago. It does federate index requests, and when you search it propagates the search request across a bunch of nodes. When my node came online it almost immediately started crawling stuff and it did get a bunch of search queries. But the network was still pretty small back then and the search results were... not great. That's the price of independence from Google's and Microsoft's giant server farms, it's hard to compete with that size.

But at the rate Google and Bing are enshittifying, I think it's worth revisiting.

Using ActivityPub for this would be immensely wasteful. It's just not feasable that all instances would have the whole index because it's so large. Back when I tried it, the network still had several TBs worth of indexed pages. This is firmly in the realm of distributed P2P systems. One could have an ActivityPub plugin however to receive updates from social media near instantly and index those immediately with less overhead. But you still want to index wikipedia, forums, blogs, whatever the crawlers can find.

Sure. SearX is a meta-search engine. It does (only) queries to other search engines to get results. YaCy on the other hand is itself a search engine. It has the data available and doesn't do queries to other engines. In theory you could combine the two concepts. Have a software that does both. But that requires some clever thinking. The returned (Google) ranking only applies to the exact search term. And it's questionable if you can store it and do anything useful with it except for when some other user searches for the exact same thing. And also the returned teaser texts are very short and tailored to the search query. So maybe also useless. It'd be hard.

One thing you could do is crawl the results that users actually click on. And I think YaCy already does that. AFAIK they had an browser add-on or a proxy or something to intercept visited pages (and hence search results).

basically requires a minimum of 20-30GB of RAM to be performant.

That's odd, the project page states 256 Megabytes and practically speaking that's nothing. Where did you find 20-30G? Are you sure you're not confusing the memory requirement with the suggested free hard drive space?

Even if it does need 32G of RAM to perform well it's not a very high hurdle. 32G of DDR4 can be had used for less than $75. Toss that in an old Core8/9 I5 Desktop, install your preferred flavor of Linux, add Docker, and you're off to the races.

I've run it in containers, never used that many resources. The whole server (running a few dozen containers) was 32gb, and it wasn't impacted in any sensible way.

That is misinformation. It doesn't need anywhere close to that amount of RAM. It's pretty much like other webapps and I used to run it on an old computer. It'll fill up your harddisk, though. If you allow it to do that.

Yea, another user has suggested passing along the request to other instances when API limits are hit. That sounds like a better model for SearXNG specifically.

There's only been about 700 yacy peers online in the last 30 days which is pretty low for a "crowd sourced" search engine, especially when many of those are, I think, temporary peers that come and go. It looks like it has only maybe 200 "master" servers which wouldn't be nearly enough to keep up with the Internet these days.

The good news is that if there's websites / urls that you care about you can point your own yacy instance at them and schedule the crawls to keep up with content changes.

I remember reading about yacy some years ago and now that I've bumped it into again it's sparked my interest. I may stand up a docker instance and play with it for awhile. If nothing else it could make a very useful "arrrrr" search engine.

I ran an instance for a while out of curiosity a few years back - building the database seemed to work fine and appeared like a good idea, had a lot of fun to see the connections with other servers and my crawler filling holes of unknown spaces. But I think the search algorithm itself was (most likely is) not sophisticated enough, it just did not give relevant results often enough, and it was extremely vulnerable to very simple SEO tactics to push trash to the top.