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Sharding is the technique of splitting the database of blockchain companies to achieve scalability and help companies process more transactions. If you want to keep things decentralized, Sharding can be a good way to scale. Another way to scale is by increasing the size of the existing database.
Sharding can help decrease the slowness of a network because it breaks a blockchain network into different shards. There are certain security concerns associated with the process of sharding as there are different ways in which shards can be attacked.
Meanwhile, horizontal scaling is another form of sharding. Horizontal scaling allows near-limitless scalability to manage big data as well as intense workloads. On the other hand, vertical scaling is increasing the power of a single server via a more powerful CPU, higher RAM, and increased storage capacity.
As we know, the more the number of users on a blockchain network, the slower the network, thus the Sharding process finds its usability here.
Sharding can be done through the horizontal segregation of databases by dividing them into rows. These rows are called Shards, which are conceptualized based on characteristics. For instance, one shard can be responsible for storing the state along with the transaction history for a certain type of address. Besides, it might be possible to divide shards on the basis of the type of digital asset they store. Transactions involving that digital asset could be done by a combination of shards.
It is worth mentioning that sharding is still in the initial testing phase of its usage in blockchain networks. Ethereum, a prominent blockchain company and the world’s second-largest cryptocurrency, is spearheading testing sharding as a probable solution to challenges associated with latency and scalability. Ethereum is likely to roll out nearly 64 new shard chains after the much-hyped “The Merge” takes place.
To combat the risk of a shard attack, Ethereum has decided to haphazardly assign nodes to specific shards and constantly reassign them at random intervals.
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