<ul><li>Data partitioning refers to the logical division of a dataset into smaller, more manageable pieces based on some criteria.</li><li>Data sharding refers to the horizontal partitioning of data across multiple physical nodes or servers in a distributed system.</li><li>Key differences between data partitioning and data sharding include scope, purpose, physical location, and independence.</li><li>Partitioning is suitable for single database systems to improve query performance, while sharding is used for scalability and fault tolerance in distributed systems.</li></ul>

Understanding Data Partitioning vs. Sharding: Key Concepts for Effective Data Management

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