| First of all, I find I kinda funny that you call banking, retail and insurance "legacy industries". I would rather be without Netflix and Google, than banking and food ... but each to their own.. While some is inertia (mostly doing to rewriting truly large applications are hard and expensive), there is also the the point that most of those industries cannot easily handle "eventually consistent" data.. Not all transactions are created equally, the hardest usually have a set of requirements called ACID. ACID in the classic RDBMS is not a random choice, but driven by real requirements of their users (the database user, i.e. applications in the business sense - and not the users as people).
The ACID properties are REALLY hard to do in scale in a distributed system with high throughput. Think of the rate of transactions in the bitcoin system (500k/day with many, many "servers") vs. visa (500M+/day) - the latter is basically driven by two (!) large mainframes (with 50ish km distance) the last I heard of any technical details. None of the companies you mention need to have strict ACID, as nobody will complain if different users see slightly different truths - hence scaling writes is faily easy. |
1: I wonder how many transactions the largest e.g Postgres clusters (or other classic RDBMS) handles per day. 500M+/day doesn't seem that incredibly high?
2: Google Spanner, which I would classify as cloudy, promises ACID guarantees at a global distributed scale. Couldn't that be used?
I've listened to a Swedish developer podcast where they interviewed an old school mainframe developer in the banking sector. He brought up similar points about the scale and correctness of database transactions, and it didn't feel convincing to me.
What does Paypal, Klarna, or even maybe Amazon give up by not using mainframes? Does any company founded in the last 10-15-20 years use mainframes? If not, does that mean that "modern" companies can't compete in these high-demand industries like retail or insurance?
I think it's much more in the inertia-point, the cost of rewriting these enormous applications is simply too large.