Making blockchains more scalable is the number one issue facing decentralized technology. Several ideas on how to effectively solve this problem have been produced, but one that persists is what is known as Sharding.
How does Sharding work?
Sharding is a method to solve scalability issues, simply by dividing the blockchain into pieces known as “shards.” This mitigates the amount of data that has to be referenced and exchanged per transaction, ultimately increasing transaction throughput.
Sharding is pretty much exactly what it sounds like. You’re taking a blockchain and breaking it into these shards, pieces of the blockchain which can be re-categorized or put into a certain neighborhood, depending on node status or geographic location. This categorization is important because once you are part of a shard, you can interact much easier with others in that shard; the data within the shard is much smaller than data contained in a full blockchain. However, sharding limits the ability to transact with an entire network. If shards are neighborhoods, then the limitation of shards is that it only lets you interact within your neighborhood.
Sharding might seem like an excellent scaling solution; however, it comes with its own set of problems. If you segment the blockchain and become part of one shard, it makes it near impossible to interact with a different shard without adding a separate protocol. Additionally, to prevent any type of double spending, you must lock your funds into a specific shard, restricting your interaction to those in the shared shard.
So while sharding might address scaling in a certain capacity, it does so in a very limiting way. Could there be specific use cases where sharding is a viable solution? Sure. Any situation where you can be restricted to one neighborhood without hindering functionality. However, the limitations facing sharding might not make the method a reasonable scaling solution for all projects.