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Just make it scale: An Aurora DSQL story

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Re: Just make it scale: An Aurora DSQL story

#41
post #32
post #31

Earlier quoted context omitted.

> one of the best parts of DynamoDB is absolute certainty on cost That depends if its On Demand or Provisioned, even if they recently added On Demand limits.

You still have absolute certainty. Read or write x amount of data and it will use exactly y R/WCU. It then just becomes a modeling problem allowing you to determine your costs upfront during design. That’s one of the most powerful features of the truly serverless products in AWS in my opinion.

Absolute certainty is challenging with a cost-based optimizer in the mix. DDB doesn't face this challenge. Although, cost for some query patterns in DDB would shift into your application layer - so you may not have exactly the cost certainty you imagine?

Would you be willing to pay more for certainty? E.g. rent the full server at peak + 20% and run at 15% utilization some of the time? Provisioned capacity or pre-committed spend seem like reasonable, but perhaps more costly, ways to get certainty.

Re: Just make it scale: An Aurora DSQL story

#42
post #38

Where can I go to read about distributed SQL and big JOINs or WHERE IN clauses? I was hoping this article would cover that elephant in the room, rather than Rust being significantly more performant than JVM languages.

Marc Brooker has written and spoken about DSQL quite a bit. It’s still rather high level. I’d expect one or more papers to come out in the next few months, similarly to other Amazon databases. https://brooker.co.za/blog/2025/04/17/decomposing.html (includes talk) https://brooker.co.za/blog/2024/12/03/aurora-dsql.html https://brooker.co.za/blog/2024/12/04/inside-dsql.html https://brooker.co.za/blog/2024/12/05/inside-d…

That's a lot of links for 0 info on distributed JOIN or WHERE IN.
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