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In what situations is data sharding recommended?

sobes.tech AI

Answer from AI

Data sharding is recommended in the following situations:

  • When the volume of data becomes too large to store and process on a single server or in a single database.
  • To improve system performance and scalability by distributing the load across multiple nodes.
  • To ensure high availability and fault tolerance, as data is distributed across different shards.
  • In systems with a high number of requests, where a single server cannot handle the load.

For example, in a large online store, sharding can be used to divide user data by regions or ID ranges to speed up query processing and reduce load on individual databases.

In what situations is data sharding recommended? — Java - sobes.tech