Sharding in MongoDB is a technique used to horizontally scale a database by distributing data across multiple servers or clusters, known as shards.
Sharding allows you to scale your database horizontally, meaning you can add more servers (shards) to the cluster to handle increased load, rather than upgrading existing hardware.
Since data is distributed, each shard is responsible for only a portion of the data, reducing the workload on individual servers.
Queries and writes can be executed in parallel across shards, leading to faster query execution and better response times.
Shards can be deployed on separate hardware, making it cost-effective to utilize commodity servers instead of scaling vertically with expensive high-end hardware.
Sharding enables geographical partitioning, allowing data to be stored on shards located close to users. This reduces latency and improves the overall user experience.
You can start with a small number of shards and gradually add more as your data grows. This makes it a flexible solution for scaling as your application evolves.
Thus overall sharding imporves performance, efficiency, scalability and cost effectiveness.