Ask HN: Scalability strategy for updating massive node trees

I created an economic engine app "Rovas"[1] that allows project owners to share rewards that their projects (A) receive, with other - "shareholder" projects (B). Individuals who work on the projects can also be shareholders. The shareholder projects (B) can also have individual and project shareholders. Rewarding one project thus might result in rewarding tens, or hundreds of thousands nodes (individuals, or projects). The rewarding act might be very frequent, in the ideal scenario maybe every second, or even faster. All rewards to individuals and projects must be recorded for audit purposes.

Example: An outdoors activities web portal has ~10^5 users, each of which is required to pay for consuming the content every time they do so, which might be daily. The portal was created by ~10 people (developers, copy writers, marketing folks,..) and uses products of other projects, like the Apache web server, MySQL database, fonts, OpenStreetMap tiles, with their own teams of developers... All of these projects and their workers share a bit of every payment made by the portal user.

Rovas is a POC that has been working for hundreds, to thousands of nodes. I chose a strategy, where a payment is not processed immediately but batched, together with other payments that arrive within (I think) 10 minutes. I am looking for an architecture/strategy to tackle the problem on a scale of millions of nodes updated frequently. I am not sure blockchain will help me given its own scalability problems, but I follow that space very sporadically and it might be the case that a similar problem is/has been solved by some implementation. Rovas is a long haul project, so even futuristic concepts interest me (quantum computing?).

[1] https://rovas.app