Hacker Newsnew | past | comments | ask | show | jobs | submitlogin

I find it interesting that there are two MongoDb Directors of Developer Relations in this thread - one former, one current - either attempting to replicate the suggested costs to see if the author's faking it, or outright blaming him he is.

Dude's got a screenshot. I doubt he faked it for the attention - he probably actually got that bill.

He feels it's expensive and he should pay less for the value he's getting considering his alternatives (Azure VMs in a 1/3 of the price).

Perhaps refer to the actual price of a billed hour there? That feels like the core theme here.



Editing a screenshot to push a narrative is pretty easy. I'm no longer with MongoDB, although still a big fan of the product, but I'm more curious as to how you could rack up a $2,500 bill just trying the product out, especially the serverless offering, coupled that with the guy being a "twitter investor", so that kicked off my BS detector.

MongoDB Atlas runs on the big 3 clouds, and of course you're going to pay more for a fully managed service, as opposed to hosting it yourself directly on the big 3, but racking up $2,500 in serverless compute charges in 24 hours seems very very hard to do, and especially by accident.


So I read your second sentence first for some reason, which seemed plausible and I wanted to respond nicely.

And then I read your first sentence - why is it always the assumption that people are going the hyperbole route? This is a well-upvoted link, with enough comments to merit a good discussion, and what appears to be a nicely-thought out post after the link.

Also, I've been following Snir for quite a while - dude wrote a massive Data Engineering roadmap which is heavily used by people learning how to ETL and has a very interesting investing blog. He's an engineer turned investor, and looks at the market from this perspective.

The derogatory quotes are unnecessary.


> racking up $2,500 in serverless compute charges in 24 hours seems very very hard to do

TBH I know how to spend that much and more with a single query (and ~30 minutes of compute time) in BigQuery. Serverless BI analytics workloads over large public datasets can do amazing things... and are also exactly the sorts of things a naive user would use to test + benchmark the capabilities of serverless data-warehousing systems.


I am not disputing the bill, just curious how he got there. He doesn't say in his post.


You're the mild one:)




Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: