zlacker

This is advice that seems reasonable but is actually pretty harmful.

Take a startup with a few users. The senior engineer decides they need pub/sub to ship a new feature. With Kafka, the team goes to learn about Kafka best practices, choose client libraries, and learn the Kafka quirks. They also need to spin up Kafka instances. They ship it in a month.

With postgres, they’ve got an MVP in a day, and shipped within a week.

>>jastr+(OP)
I can set up an application to use AWS SQS or GCP PubSub in a day and it will scale without a second thought. I don't think it's productive to compare the worst case of scenario A and the best case of scenario B.

>>jastr+(OP)
> With postgres, they’ve got an MVP in a day, and shipped within a week.

And the next week they realize they want reader processes to block until there is work to do. Oops that's not supported. Now you have to code that feature yourself... and soon you're reinventing Kafka.

>>jastr+(OP)
How does any of this equally not apply to PostgreSQL ?

Is this some magical database where you don't need to worry about access patterns, best practices or how it is deployed.

>>threes+Wb
Yes, it's that magical database, up to certain scale.

>>petilo+E4
That's where LISTEN comes in. It's very simple to write this loop perfectly correct.

>>petilo+E4
The very source we're talking about describes how to block until there is work to do -- listener.Listen("ci_jobs_status_channel")

>>threes+Wb
> How does any of this equally not apply to PostgreSQL ?

1. Postgres is easier to setup and run (than Kafka) 2. Most shops already have Postgres running (TFA is targeted to these shops) 3. Postgres is easier to adapt to changing access patterns (than Kafka).

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> Is this some magical ...

Why must your adversary (Postgres) meet some mythical standard when your fighter (Kafka) doesn't meet even basic standards.