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>What does Paypal, Klarna, or even maybe Amazon give up by not using mainframes?

Simplicity. Because instead of having an enormous team to maintain their multi-million line Kubernetes configuration files that automatically spawns thousands of servers, having an enormous team that tries to fix the CAP problem, you go grab IBM, you tell them "this mainframe goes down, you're dead, here's half a billion in cash" and you run all of your software on a single, massive machine.

Sure, it adds other problems, but to be fair I'd rather deal with a mainframe than yet another microservice that doesn't work because Omega Star doesn't handle ISO timestamps and it blocks Galactus

>Does any company founded in the last 10-15-20 years use mainframes?

The biggest issue with mainframes are:

- High initial costs (although that's been changing)

- Nobody knows how to work on IBM Z mainframes

- The current zeitgeist about having a billion servers spread throughout the world because it's really important to have an edge CDN server for your cat trading card game

These industries didn't care about that because they could absorb these high initial costs, had the knowledge of the people building the mainframes, and were already highly centralized. Decentralization just adds more problems, it doesn't fix anything.

>I think it's much more in the inertia-point, the cost of rewriting these enormous applications is simply too large.

Rewriting just because it's not following the latest trend is garbage. These applications work. They're not going to work better because you're using Spanner now.

Remember inertia goes both ways. As soon as you have a large system "in the cloud" or otherwise "distributed" (also only in your shed).

Rewriting your system to a mainframe architecture is equally as expensive.

Lets say that you save a hundred megabucks per year by going cloud (I am really not convinced, that you save any money at all, but lets say). That is what 1500 man-years of work? No way you can rewrite even a simple "banking" system in that amount of work, and the second problem is that you need to feature-freeze the old system (and hence your business) while you convert. So maybe 5 to 10 years of lost competitive power on top of that..

Also, remember these are not "begin work; select * from table where id = 123; commit;" transactions. These have maybe 50 to 200 queries (selects and updates) in each transaction (has the paying party the funds, is the receiving party blacklisted (terror organisation for example), does this look like money laundring.... etc... and a very detailed logging requirement by law). All of these MUST usually be in the same "snapshot" (in the RDBMS definition).

It makes no sense to talk about "transaction rates" without an intimate knowledge of what it does, as especially marketing departments have a tendency to use the simplest possible "transactions" to get a large number..

And in the end, it is only "money" the might loose, and any choice you make makes some other choices in the future easier (and some harder). That is called path dependency.

I agree, it's obviously very hard to compare transaction rates, and I also agree that I have hard time seeing companies currently using mainframes recouping the cost of migrating. If it works, it works.

But.

> Rewriting your system to a mainframe architecture is equally as expensive.

There was a new bank mentioned in this thread that actually started using mainframes from scratch, but other than that I've never heard of any "modern" fintech (or really any) company introducing mainframes. Organisations actually rewriting functioning systems TO mainframe must be almost never heard of (in the last 10-20 years at least).

If System Z, Cobol and DB2 are so obviously superior, why are so many successful new competitors in industries where they are the norm in older companies choosing to not use them?

I'm not saying banks should rewrite their stuff in node.js (or deno - even better of course), it makes sense for them to stay.

I just have a hard time believing that mainframe systems are so technically impressive, to the point where some people claim it's almost impossible to build a similar system on non-mainframe technologies.

The software on mainframes only shines in reliability and the fact that the machines have been build for money transaction from the start. For example doing "decimal" math (if you think python) is as inexpensive as doing float math due to hardware support.

The machines themselves are impressive (hardware wise) and reliability wise, for example you can swap mainboards one by one in a full frame without ever taking down the machine (think raid on a mainboard level, RAIMB ?).

But the high start-up cost makes most startups going the other road. I am not convinced that the vertically scaling is cheaper than horizontally, if you need the ACID guarantees... but it is hard to say.

The reason why us old dogs say it is hard (not impossible) is due to the single-image and acid requirements. There is no good way to do that distributed (look up the CAP theorem).

So having a massive computer (with double digit terabytes of memory AND cache, and truly massive i/o pipes.. just makes building the need-to-work stuff simpler.

As an example, a few years ago I was (on my own money) on a mainframe conference (not doing mainframe work in my work day).. at that time the machine had more bandwidth to the roughly 200 PCIe adapters that a top-of-the-line intel CPU had between the L1 cache and the computing cores) - and that meant that given enough ssd's you could move more data into the system from disk that you could move into an intel cpu from cache...

Also mainframes can run two mainframes lockstep (as long as they are less than 50km apart), that means if one of them dies during a transaction (which in itself is extremely rare), the other can complete it without the application being any the wiser.. Try that in the cloud :)

I've worked at three banks and it's not about cost. It's because they aren't stupid.

Young developers often think that banks, insurance companies etc. should just rewrite these "legacy" systems because it will bring all of these magical benefits with no risk. Whereas older developers who have worked on (a) mission-critical applications, (b) major re-platforming efforts and (c) projects in a highly regulated industry know the score.

Doing just one is hard. Doing all three at the same time is suicidal. The chance of project success is basically in the single digits. And the risk of failure is billions in lost revenue and your future prospects in the company and within the broader industry ruined.

Not so sure, experienced tech managers are also very wary of vendor lock-in and tech debt which mainframes give you in spades.

The vendor lock-in is a feature to them. They're not a tech company. They're banks. They're insurances. Lock-in means they can send a lot of cash to someone and the problem gets fixed, which is the only thing they care about. And in good news, cash is also a thing they have a lot of. The cost of their tech infrastructure is a blip on the radar compared to payroll, to the cost of their physical spaces.

I assume from this comment that you've never worked in the enterprise.

Because (a) major decisions like choosing a mainframe are not made by tech managers and (b) every company is built around vendor lock-in.

Who do you think companies like Atlassian, Oracle, Salesforce etc sell to ?

It's a little off to think that a mainframe was "chosen". Software and the companies that write it and support it "chose" the hardware for you.

Google internally announced a while back that Bigtable (which powers Spanner etc.) hit 1B queries/second -- there definitely exist systems with far larger scale (though admittedly this is with lower atomicity requirements and probably includes reads etc.).

VISA does 500m+ transactions per day and Spanner does 1B queries per day, but it's quite unlikely that what a transaction means on VISA is the same as what a query means on Spanner.

Spanner does over 1B queries per SECOND (but your other point still stands of course)

If it is readonly shared-nothing queries, I am sure the hardware I have in my flat can do that as well..

The hard parts are updates in a shared system with a single consistent "view" requirement..

The hardware in your flat definitely cannot do 1 billion queries per second -- that requires a massive, global system, which can probably also support a shared system with ~100,000x less queries.

That sounds so impressive I googled it. It's actually 6 billion queries per second: https://id.cloud-ace.com/how-youtube-uses-bigtable-to-power-...

But then I mulled over it for a while, and it occurred to me it's likely Sqlite does orders of magnitude more than that planet wide.

Spanner's 1 billion per second is more impressive: https://cloud.google.com/blog/topics/developers-practitioner..., assuming it's returning a consistent view across many tables. But the Sqlite comparison still stands.

Visa claims 24,000 TPS, but in reality runs at a 10'th of that. It would be interesting to see if Spanner could process the same 2,000 transactions per second. Sqlite definitely can't.

Amazon does use mainframes. They aren't a payment processor and don't handle that part of the processing. That's why the likes of VISA get to charge their fee.