Sharding is a technique of partitioning database tables by row ("horizontally"); typically this technique requires a key to be selected that determines how the rows are to be partitioned.

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In one way, sharding is the best way to scale. Sharding enables you to linearly scale your database’s cpu, memory, and disk resources by separating your database into smaller parts. In other ways, sharding is a controversial topic.


Sharding is one of those database topics that most developers have a distant understanding of, but the details aren’t always perfectly clear unless you’ve implemented sharding yourself.


Version 10 of PostgreSQL added the declarative table partitioning feature. In version 11 (currently in beta), you can combine this with foreign data wrappers, providing a mechanism to natively shard your tables across multiple PostgreSQL servers.


Can database-style sharding improve the performance of a multi-threaded C# application? This tutorial talks about the performance bottlenecks in sophisticated C# concurrency operations and how sharding can solve these issues.