@braden: We haven’t had that much feedback from elsewhere in the community, but I’m inclined to believe that others will share @blarghmatey’s concerns about HA. It’s unlikely to change what goes out in the Sumac timeframe, but I think it’s worth Axim’s while to fund an investigation to the memory usage issues around Typesense.
I agree with both of you that the memory usage is the biggest potential drawback of Typesense, but I’m not sure how that will actually play out in practice. My intuition is that because Meilisearch uses memory mapped files, and because relatively few parts of the index will be “hot” at any given time, that it will effectively require less memory for comparable performance. But there are some huge caveats with that:
- My intuition is purely guesswork–it could be that Meilisearch requires comparable RAM to Typesense to give acceptable performance in practice on large datasets.
- Running in clustered mode will increase indexing write latencies. By how much?
- Are there significant differences in how compactly they represent their indexes?
The two biggest things that I’m aware of are course content data storage and forums post storage (the catalog-related metadata that I know of is orders of magnitude smaller).
@blarghmatey: If someone coded a minimal Typesense integration (using the interface that @qasimgulzar is making), would you have the time/capacity to be able to run both Typesense and Meilisearch indexing against the data on your production site? So that we can get a better understanding on how memory and latency compare across the two using real data?