concept

Database Sharding

Database sharding is a horizontal partitioning technique that splits a large database into smaller, more manageable pieces called shards, each stored on separate database servers. It distributes data across multiple machines to improve scalability, performance, and availability by reducing the load on any single server. This approach is commonly used in distributed database systems to handle massive datasets and high transaction volumes.

Also known as: Sharding, Horizontal Partitioning, Data Partitioning, Database Partitioning, Shard
🧊Why learn Database Sharding?

Developers should learn and use database sharding when building applications that require handling large-scale data or high-throughput workloads, such as social media platforms, e-commerce sites, or real-time analytics systems. It is essential for achieving horizontal scalability beyond the limits of a single database server, reducing latency, and ensuring fault tolerance by isolating failures to individual shards.

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