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Meilisearch – search engine API bringing AI-powered hybrid search

(github.com)
151 points modinfo | 2 comments | 14 Apr 25 12:46 UTC | HN request time: 0.526s | source
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be_erik ◴[14 Apr 25 14:00 UTC] No.43681389[source]▶
Is meilisearch ready for production workloads? I would love to use some of the feature set, but is the only option for HA running multiple instances and keeping them in sync?
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Kerollmops ◴[14 Apr 25 14:48 UTC] No.43681927[source]▶
Meilisearch has been production-ready since v1.0. I made it in Rust to ensure it stays production-ready for years and years. Memory-safe languages are here to replace unsafe ones like C++ and reduce the number of breaches you expose in production.

Here is an article by Google showing the benefits of using memory-safe languages in production rather than others. It is explicitly rotating around Rust [1].

[1]: https://www.chromium.org/Home/chromium-security/memory-safet...

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arccy ◴[14 Apr 25 15:27 UTC] No.43682364[source]▶
This reply doesn't inspire confidence at all...

Made in Rust isn't a magic bullet to be production ready, and I'd be more concerned about logic bugs rather than CVEs.

1.0 is like the bare minimum to be used in production, but that doesn't necessarily mean it's been battle tested enough to be considered production ready.

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Kerollmops ◴[15 Apr 25 07:25 UTC] No.43689933[source]▶
HuggingFace is using Meilisearch, in production, on their website for a year now.
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1. holysantamaria ◴[15 Apr 25 08:20 UTC] No.43690267[source]▶
And it takes 360ms to get an answer from their server (not fulltext, quicksearch api endpoint). And 2ms to download the results on the network.

Is this the instant search that you are advertising on your website?

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2. Kerollmops ◴[15 Apr 25 08:31 UTC] No.43690343[source]▶
V1.14, released yesterday [1], ships with a search embedding cache. Most of the time you see is spent waiting for an OpenAI embedding answer. We also just shipped composite embedders to reduce the network latency when you need to respond quickly to user searches (by running embedders on the Meilisearch server) but still use external APIs to index many documents in batches. Note that it can only work with open-source embedders, the ones HuggingFace serves.

[1]: https://github.com/meilisearch/meilisearch/releases/tag/v1.1...