> not the best design [...]
So those engineers at Shopify worked hard for months on a more performant system, but they missed the obvious structure? They chose a complex denormalization for no good reason?
It may be true, but I think it's presumptuous to belittle their work when we have only partial information. My guess is that they had good reasons to think that the more obvious ways would not scale.
And from reading your comments in this thread, I believe your structure would fail at their scale. A SQL query that uses 2 sub-queries with "group by" is probably too heavy. From the post, at peaks there would be millions of active shopping carts.
BTW, I suspect most orders are just for 1 or 2 of each item, so the denormalization is not as heavy as it seems.
You might not have noticed that essentially the entire blog post was AI written.
There's even this bit where they discover a remarkable trick:
> Each round trip to the database has a cost. For carts with multiple line items, we batch reservation queries using UNION ALL so we fetch all needed units in one round trip
Insights like that really don't read like senior level output, and of course, it's LLM output. I'm not sure it's presumptuous to question it.
i also work in big tech and know that a lot of bullshit design creeps into system design and prod, because everyone is overworked, overstressed, wants to just get things done for the quarterly performance review as to not get shitcanned with severance
re concurrency, it is not a big issue at all. stock exchanges deal with HFT traders and can easily deal with concurrency of orders. Same can be implemented with shopify, but I doubt they face the same level of concurrency as stock exchange anywhere near