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570 points davidgu | 9 comments | | HN request time: 1.304s | source | bottom
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sorentwo ◴[] No.44525509[source]
Postgres LISTEN/NOTIFY was a consistent pain point for Oban (background job processing framework for Elixir) for a while. The payload size limitations and connection pooler issues alone would cause subtle breakage.

It was particularly ironic because Elixir has a fantastic distribution and pubsub story thanks to distributed Erlang. That’s much more commonly used in apps now compared to 5 or so years ago when 40-50% of apps didn’t weren’t clustered. Thanks to the rise of platforms like Fly that made it easier, and the decline of Heroku that made it nearly impossible.

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1. alberth ◴[] No.44526115[source]
I didn’t realize Oban didn’t use Mnesia (Erlang built-in).
replies(1): >>44526299 #
2. sorentwo ◴[] No.44526299[source]
Very very few applications use mnsesia. There’s absolutely no way I would recommend it over Postgres.
replies(3): >>44526730 #>>44527665 #>>44528009 #
3. arcanemachiner ◴[] No.44526730[source]
I have heard the mnesia is very unreliable, which is a damn shame.

I wonder if that is fixable, or just inherent to its design.

replies(1): >>44527065 #
4. sb8244 ◴[] No.44527065{3}[source]
My understanding is that mnesia is sort of a relic. Really hard to work with and lots of edge / failure cases.

I'm not sure if it should be salvaged?

5. asg0451 ◴[] No.44527665[source]
can you explain why?
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6. tecleandor ◴[] No.44528009[source]
I think RabbitMQ still uses by default for its metadata storage. Is it problematic?
replies(1): >>44528351 #
7. spooneybarger ◴[] No.44528019{3}[source]
Mnesia along with clustering was a recipe for split brain disasters a few years ago I assume that hasn't been addressed.
8. schaum ◴[] No.44528351{3}[source]
They are in the process of migrating away from it https://www.rabbitmq.com/docs/metadata-store
9. ahoka ◴[] No.44531214{3}[source]
I have only worked with a product that used it, so no direct experience, but one problem that was often mentioned is split-brains happening very frequently.