The history tells that a single RDBMS node cannot handle tons of traffics on web system which come from all over the world, no matter how the database is tuned. MySQL has implemented a master/slave style replication built-in for long time, and it has enabled web applications to handle traffics using a scale-out strategy. Having many slaves has been suitable for web sites where most of traffics are reads. Thus, MySQL's master/slave replication has been used on many web sites, and is being used still.
However, when a site grow large, amount of traffic may exceed the replication's capacity. In such a case, people may use memcached. It's an in-memory, very fast and well-known KVS, key value store, and its read throughput is far better than MySQL. It's been used as a cache for web applications to store 'hot' data with MySQL as a back-end storage, as it can reduce read requests to MySQL dramatically.
While 1:N replication can scale read workload and memcached can reduce read requests, it cannot ease write load well. So, write traffic gets higher and higher when a web site becomes huge. On such web sites, a technique called "Sharding" has been used; it's a technique that the application choose an appropriate MySQL server from several servers.
In that way, MySQL+memcached has been a de-fact standard data store on huge web sites for long time.