[jph]

Clever idea, good work!

You asked for feedback: I see opportunities for you to nail the basics, by focusing on the value proposition so business-oriented people understand why/how to buy, and on the the middle-tier architecture so technical people understand that you're akin to OpenSearch with Faiss & vectors that auto-update.

My understanding (and please clarify as you wish) of what I've read on your site is this: you're selling the hosted version for enterprises at a price to be discussed with your sales team, and the architecture is something like this...

  ┌──────────────┐    ┌───────────────┐    ┌──────────────┐
  │Search SDK    │    │Search Engine  │    │Data Source   │
  │• Typescript  │    │• OpenSearch   │    │• Postgres    │
  │• Python      │    │• Faiss, KNN   │    │• MySQL (?)   │
  │• Java (soon) │◀──▶│• Keyword, BM25│◀──▶│• Oracle (?)  │
  │• Go (soon)   │    │• Auto-update  │    │• Mongo (?)   │
  │• Etc.        │    │• Etc.         │    │• Etc.        │
  └──────────────┘    └───────────────┘    └──────────────┘

[pnoel]

That's a nice diagram! Yeah that's roughly it. We'll be adding support for more sources of truth in the future to expand coverage, like the ones you mention but also NoSQL like MongoDB

[isaacfung]

So are you guys using faiss instead of the vector search of postgres?

I think vespa also supports hybrid search(it can also use late interaction model like colbert). How is retake compared to vespa?

Will retake supports sparse vector models like SPLADE(I heard they solve the vocab mismatch problems of keyword search).

How do you guys implement filtering?

[retakeming]

1. Correct - we don't rely on pgvector. As a result, we're compatible with more existing managed Postgres services.

2. Probably the biggest differentiator between Vespa and Retake is the core architecture - Retake is built on top of OpenSearch. There's been quite a bit of debate regarding different search engines since Yahoo released Vespa - we leaned into OpenSearch because we saw that Open/ElasticSearch and its query language was much more familiar to more developers. Something that's coming soon to Retake is the ability to control how keyword/semantic scores are normalized and combined, which should give developers more fine-tuned control over their results.

3. In the short term, our support for models like SPLADE is constrained by OpenSearch, which uses BM25. In the medium to long term we would definitely consider modifying OpenSearch to do stuff like this.

4. We support both post-filtering and efficient kNN filtering, which takes place during the kNN search and guarantees that k results are returned. More details on the faiss kNN filter implementation can be found on the OpenSearch docs: https://opensearch.org/docs/latest/search-plugins/knn/filter...

[noodlesUK]

Unrelated to OP, but how did you create that diagram?

[gregsadetsky]

  ╔═════════════════════════════════════════════════════╗
  ║                                                     ║
  ║ https://en.wikipedia.org/wiki/Box-drawing_character ║
  ║                                                     ║
  ╚═════════════════════════════════════════════════════╝

:-)

there was a related thread a few days ago: https://news.ycombinator.com/item?id=37040883

you could use https://asciiflow.com/ (web) or https://monodraw.helftone.com/ (mac) to make such diagrams and paste them here.

use the "code" formatting ("Text after a blank line that is indented by two or more spaces") -- see https://news.ycombinator.com/formatdoc