What is the difference between Redis clustering and sharding?

What is the difference between Redis clustering and sharding?

Redis clustering is a way to distribute data across multiple Redis nodes, allowing for horizontal scaling and high availability. Sharding, on the other hand, is a method of partitioning data across different databases or instances to improve performance and manageability.

Can you explain how Redis clustering works?

Sure! Redis clustering allows you to split your dataset into smaller subsets, called slots, which are distributed across multiple nodes. Each node is responsible for a subset of these slots, enabling the system to handle more data and requests.

What are the advantages of using sharding?

Sharding helps improve performance by distributing the load across multiple servers, reduces the risk of data loss, and allows for easier management of large datasets.

Are there any downsides to using Redis clustering?

Yes, some downsides include increased complexity in setup and management, potential for data inconsistency during partitioning, and the need for careful planning of data distribution.