The question is not "is Meilisearch better than Elasticsearch." It's the wrong frame. The question is: does your search use case require the general-purpose power of a distributed analytics engine, or does it require fast, typo-tolerant, faceted search over a bounded dataset? Be honest about the answer, and pick accordingly.
I also wanted features like hot-reloading (being able to load new versions of the code without restarting the program/losing runtime state). Cakelisp made it possible to implement hot-reloading entirely in "user-space", thanks to code modification.
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In both cases I'll be adding custom code that could fail. The webhook needs a sidecar container that checks if the job finishes and sends a fetch request. You might say "well that sounds pretty easy" and it is. Until for some reason it fails because some dependency was missing or the Kubernetes JSON was incorrectly formatted or a multiplicity of reasons and you get a job that never ends on the UI. The polling is the same. Jobs can end in multiple different states and you have to account for all of them.
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