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Re:Pulsar vs. Kafka by doctor_eval on Friday July 10, 2020 @07:43AM (#23790515)
> Lower end-to-end latency helps enterprises gain business insights faster.

They lost me here. I can think of plenty of situations where reduced latency is beneficial, but not many situations where shaving a few milliseconds would make a difference to “business insight”!

Although I suppose it is strictly correct, in the tautological sense...

Re:Pulsar vs. Kafka by willvarfar on Friday July 10, 2020 @08:58AM (#23790999)
So I've developed an in-house fancy thoroughbred 'real time' data warehouse, a very rare beast indeed, and its awesome.

Of course, our business is still running on nightly reports. But the tech is cool!

So I wanna say you're wrong, but I've got man-years invested in a system that hasn't been utilized to its full potential yet :(

Time will tell. Somewhere, some competitor will be using real-time insights to out-compete us.

Re:Pulsar vs. Kafka by nikhilsimha on Friday July 10, 2020 @12:29PM (#23793205)
Nightly to seconds is definitely great. Seconds to milliseconds is what is questionable I think.
Re:Pulsar vs. Kafka by throwaway_pdp09 on Friday July 10, 2020 @12:52PM (#23793500)
> Nightly to seconds is definitely great

Why? Can a business mobilise in anything less than days? If a report is minutes out of data, is that any loss? Given that some largish proportion of reports are never used, perhaps better management is key.

not disagreeing but efficiency is not just a matter of quickness.

Re:Pulsar vs. Kafka by atomicity on Friday July 10, 2020 @03:36PM (#23795449)
Nightly to seconds = developers can see the data generated within seconds.

This generally has implications on data quality, because you aren't fixing data quality issues once they occur in prod.

This also makes it far easier to develop ETL pipelines. You don't need complex tooling to see whether your ETL pipeline works.

You can technically fix data quality and dev velocity issues without low data freshness, but a quick glance at the data engineering landscape tells you they aren't being solved enough.

Re:Pulsar vs. Kafka by olavgg on Monday July 13, 2020 @08:04AM (#23819833)
I work in oil and gas with process optimization, and we are working on autonomous tuning of the production process in a way that is not possible with daily data updates and manual human intervention.

Quite simply, the end goal is increased oil production and reduced power consumption. Realtime data flows are a big deal when reading from thousands of sensors for just one process system and there are hundreds of tunable parameters. All this has to be safe also.

Re:Pulsar vs. Kafka by itestyourcode on Friday July 10, 2020 @10:22AM (#23791730)
I agree shaving dozens or hundreds milliseconds of latency is hardly noticeable to end users. But latency is an indicator of how well the system can perform and scale up. Signs of high latency under normal load can reveal design or implementation flaws in the software (supposedly running on any modern hardware) Ultimately you want a system can scale up and delivers consistent latency. Therefore, a low and consistent latency is a health-meter to assure that. Within the same cluster (no network I/O), Pulsar has pretty impressive 5ms pub/sub latency for persistent topics (including written to and acknowledged by the non-volatile disk)
Re:Pulsar vs. Kafka by kjeetgill on Friday July 10, 2020 @12:03PM (#23792914)
I agree with everything you're saying about the value of reduced/smoothed out latencies and I suspect the parent agrees with that as well, but the parent was mostly teasing about the choice of "business insights" in lieu of all you've mentioned.