Regardless, clustering, replication, and sharding each have pros and cons that should be weighed heavily before embarking on an individual strategy.
And because sharding is done at the application layer, you can do it for databases that don't support regular partitioning.
Standard JPA has no effective means of dealing with sharding or portioning as the specification implicitly assumes a single database as the repository.
In the right situation, sharding could be key to unlocking scale and speed in a traditional RDBMS.
As I mentioned earlier, sharding forces you to be keenly aware of primary keys, as you'll manage them yourself.
Database sharding provides many advantages, such as faster reads and writes to the database, improved search response, smaller table sizes, and distribution of tables based on need.
Because sharding isn't a native database technique - that is, you must implement it in your application - you'll need to map out your sharding strategy before you begin.
Next, I need to verify that my sharding implementation works.
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