Which of the following is a key benefit of sharding in database management?

Which of the following is a key benefit of sharding in database management?

• A. Increased overall database complexity
• B. Scalability through independent updates
• C. Decreased retrieval speed of data
• D. Limiting data redundancy across databases

Answer: (B)

Sharding is a database architecture pattern where data is partitioned into smaller, more manageable pieces, called shards, that can be distributed across multiple database servers. One of the key benefits of sharding is scalability through independent updates. This means that each shard can be updated, queried, and managed independently of the others, allowing for better performance as the database grows. When the load increases, additional shards can be added without affecting the performance of other existing shards, enabling horizontal scalability. This approach helps to accommodate larger datasets and higher transaction volumes without bottlenecking a single server. The other options do not reflect the advantages derived from sharding. Increased overall database complexity is generally a disadvantage, as managing multiple shards typically requires more sophisticated infrastructure and maintenance. Decreased retrieval speed of data contradicts the intent of sharding, which aims to improve performance through parallel processing. Limiting data redundancy across databases is not a primary goal of sharding; instead, the focus is on distributing the data more efficiently while keeping redundancy manageable within shards.

Sharding is a database architecture pattern where data is partitioned into smaller, more manageable pieces, called shards, that can be distributed across multiple database servers. One of the key benefits of sharding is scalability through independent updates. This means that each shard can be updated, queried, and managed independently of the others, allowing for better performance as the database grows. When the load increases, additional shards can be added without affecting the performance of other existing shards, enabling horizontal scalability. This approach helps to accommodate larger datasets and higher transaction volumes without bottlenecking a single server.

The other options do not reflect the advantages derived from sharding. Increased overall database complexity is generally a disadvantage, as managing multiple shards typically requires more sophisticated infrastructure and maintenance. Decreased retrieval speed of data contradicts the intent of sharding, which aims to improve performance through parallel processing. Limiting data redundancy across databases is not a primary goal of sharding; instead, the focus is on distributing the data more efficiently while keeping redundancy manageable within shards.