Four Data Sharding Strategies We Analyzed in Building a Distributed SQL Database

YugabyteDB uses various data sharding strategies including algorithmic, linear hash, consistent hash, and range sharding. Algorithmic and linear hash sharding are not recommended due to their limitations and potential performance issues. Consistent hash sharding is ideal for massively scalable workloads as it distributes data evenly across nodes while maintaining an explicit mapping table. Range sharding is useful for performing range searches but can lead to scalability bottlenecks if not implemented correctly. YugabyteDB supports both consistent hash and range sharding, with hash sharding as the default, allowing users full control over how to shard their data. The choice of sharding strategy depends on the specific use case and requirements of the application.

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