[breadwinner]

Use case is "user-facing analytics", for example consider ordering food from Uber Eats. You have thousands of concurrent users, latency should be in milliseconds, and things like delivery time estimate must updated in real-time.

Spark can do analysis on huge quantities of data, and so can Microsoft Fabric. What Pinot can do that those tools can't is extremely low latency (milliseconds vs. seconds), concurrency (1000s of queries per second), and ability to update data in real-time.

Excellent intro video on Pinot: https://www.youtube.com/watch?v=_lqdfq2c9cQ

[listenallyall]

I don't think Uber's estimated time-to-arrival is a statistic on which a database vendor, or development team, should brag about. It's horribly imprecise.

[akavi]

Also isn't something that a (geo)sharded postgres DB with the appropriate indexes couldn't handle with aplomb. Number of orders to a given restaurant can't be more than a dozen a minute or so.

[SoftTalker]

Especially as restaurants have a limit on their capacity to prepare food. You can't just spin up another instance of a staffed kitchen. Do these mobile-food-ordering apps include any kind of backdown on order acceptance e.g. "Joe's Diner is too busy right now, do you want to wait or try someplace else?"

[codetrotter]

Sometimes you’ll also have a situation where your food is prepared quickly but no drivers want to pick up the food for a while.

At least it used to be like that a few years ago.

https://www.reddit.com/r/UberEATS/comments/nucd2x/no_tip_no_...

https://www.reddit.com/r/UberEATS/comments/rtn2xe/no_tip_no_...

https://www.reddit.com/r/UberEATS/comments/uce6cs/orders_sit...

https://www.reddit.com/r/doordash/comments/17ojre0/doordash_...

https://www.reddit.com/r/doordash/comments/np6rik/you_have_e...

https://www.reddit.com/r/doordash/comments/o32nl4/no_tip_ord...

Don’t know if the situation has improved since.

The reason this happens is because Uber Eats and DoorDash and others have/had this concept where you’d “tip” for the delivery. Which is actually not a tip, but just a shitty way of disguising delivery fees and putting customers against the people that deliver the food. But that in turn has its background in how the restaurant business treats their workers in the USA, which has been wacky even long before these food delivery apps became a thing.

Anyway, regardless of your opinion on “tipping” and these practices the point was to say that there are additional complications with how much time it will take for your order to arrive aside from just the time it takes to prepare the food and the time it takes to travel from the restaurant to your door, even when the food has been prepared and a delivery driver is right there at the restaurant. If the “tip” is too low, or zero, your order could be left sitting on the shelf with nobody willing to pick it up. At least a few years ago it was like that.

[cyanydeez]

What about it's ability to choose pricing based on source-destination and projected incomes.

[listenallyall]

All you need for this is a dictionary of zip codes and a rating -- normal, high, very high. Given that ZIPs are 5 digits, that's 100,000 records max, just keep it in memory, you don't even need entries for the "normal" ZIPs. Even if you went street-level, I doubt you'd catalog more than a few hundred thousand streets whose income is significantly more than the surrounding area.

All of this ignores the fact that adjusting a restaurant's prices by the customer's expected ability to pay often leads to killing demand among your most frequent and desirable clientele, but that's a different story.