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The most important aspect of a scalable web architecture is data partitioning. Most components in a modern data center are completely stateless, meaning they just do batches of work that is handed to them, but don't store any data long-term. This is true of most web application servers, caches like memcached, and all of the network infrastructure that connects them. Data storage is becoming a specialized function, delegated most often to relational databases. This makes sense, because stateless servers are easiest to scale - you just keep adding more. Since they don't store anything, failures are easy to handle too - just take it out of rotation.

Stateful servers require more careful attention. If you are storing all of your data in a relational database, and the load on that database exceeds its capacity, there is no automatic solution that allows you to simply add more hardware and scale up. (One day, there will be, but that's for another post). In the meantime, most websites are building their own scalable clusters using sharding.

The idea behind sharding is simple: split the data between multiple machines, and have a way to make sure that you always access data from the right place. For example, consider this simple scheme. Imagine you want to store data about customers, each of whom has "last name" field in your database. You could create 26 identical databases, and assign each of them a letter of the alphabet. Then, whenever you want to look up data about John Smith, you first connect to the "S" database, and then fetch the data you want. All of the sudden, your single database solution just got twenty-six times more capacity added to it.



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