I would add that software infrastructure can run incredibly fast and scale incredibly well on modern hardware if you're a bit careful about resource usage. Tra

I would add that software infrastructure can run incredibly fast and scale incredibly well on modern hardware if you're a bit careful about resource usage. Traditional relational DBs like Postgresql are very scalable on modern hardware. If you take the time to craft a normalized schema with low redundancy being careful about keeping data small, you can achieve performance and resource efficiency and cache efficiency hundreds of time better than bloated distributed document nosql based systems. You can also get better transactional integrity, reduce reliance on queues (use load balancers instead) and get more instant and more atomic error propagation and edge case resolution. You can really build something lean and mean to a point that would be physically impossible in distributed systems or systems that involve multiple hops over potentially congested networks (as Admiral Grace Hopper likes to remind us, distance matters in computing https://www.youtube.com/watch?v=9eyFDBPk4Yw https://www.youtube.com/watch?v=9eyFDBPk4Yw). As far as I know, normalized relational databases are still the best at efficiently using multiple levels of physically near caches to their full potential. Most applications don't need to scale horizontally and can easily fit on single servers (that can scale to dozens of cores and terabytes of ram). I hear arguments that it's the engineers that are expensive so it's ok to be wasteful with hardware if it saves engineering time but in my experience the type of engineers that are good at optimizations are often good at engineering in general and the ones that forget to think about efficiency are also sloppy with other things. It doesn't mean you have to write your code in C. Very fast code can be written in high level languages with the proper skills (See projects like Fastify).