This is simply not true. I work for a major internet company that has millions of users. We use SQL for all of our data (images and SWFs excepted, of course). We do all logging to SQL tables. We use key-value cache servers for hot, non-relational data, but we don't have a lot of that.
We built most of our data center with cheap hardware. It is quite possible that we splurged on a load balancer and some other funky networking gadgets; I don't know. We did, however build quite a lot of custom software to abstract away the fact that we have split our data among dozens of machines. This is essentially the work of two people (one hardware, one software). Finding the people who can build such a system is difficult, to put it mildly, but once you find them, you don't need deep pockets.
Reddit is another example of a site that runs on SQL. Part of the problem with the "SQL won't scale" argument is that essentially all of the live queries function like key-value lookups (or lookups against a very small number of rows). If you're tempted to do something insane like service a request with a join, then you're doing it wrong and you need to cache.
Lookups by index will have the same performance characteristics no matter what. It doesn't matter if you're using a Python dict, an index in MySQL, or a key-value store.
We built most of our data center with cheap hardware. It is quite possible that we splurged on a load balancer and some other funky networking gadgets; I don't know. We did, however build quite a lot of custom software to abstract away the fact that we have split our data among dozens of machines. This is essentially the work of two people (one hardware, one software). Finding the people who can build such a system is difficult, to put it mildly, but once you find them, you don't need deep pockets.
Reddit is another example of a site that runs on SQL. Part of the problem with the "SQL won't scale" argument is that essentially all of the live queries function like key-value lookups (or lookups against a very small number of rows). If you're tempted to do something insane like service a request with a join, then you're doing it wrong and you need to cache.
Lookups by index will have the same performance characteristics no matter what. It doesn't matter if you're using a Python dict, an index in MySQL, or a key-value store.
THEY ARE ALL O(1).