How does this compare to full text search in Postgres?

Great blog post! First one I've seen with good comparisons to the other options. I would recommend adding Xapiand too: https://github.com/Kronuz/Xapiand

Thanks (you can upvote it here if you want: https://news.ycombinator.com/item?id=19605334 )

I've added a mention of Xapian/Xapiand as well now and generated new graphs that include data for those two projects.

Where the heck is manticore?

Fork of Sphinx Search with a support team around it from my understanding.

I understand what it is but I'm not sure why it wasn't included. They forked specifically because nothing was happening in sphinx and they've been releasing new features.

Good point; I've added it now, both to the blog post and to the graph: https://blog.minimum.se/assets/elasticsearch-open-source-com...

I read that as "What" not "where", sorry.

Vespa.ai is the Number 1. And I get behind it, from a previous ElasticSearch user , Vespa is amazing!!!

Would you be willing to expand on this a bit? We run multiple elasticsearch clusters and there are pain points everywhere, I wonder where vespa improves?

For us, Vespa It is in a different league. Some quick things I remember: - Native Tensor/ XGBoost support - Automatic data partitioning and auto balancing( no need to set shards before hand) - Jdisk (https://docs.vespa.ai/documentation/jdisc/) - This is the major feature for us. It enables us to create Distributed Applications that manipulate the search results directly on the nodes.

I'm not associated with the team, but I take every opportunity to promote it, as I think it is a very underrated project.