Which database has better support for parallel processing: Postgresql or MySQL?

When it comes to parallel processing, PostgreSQL generally has an edge over MySQL due to its advanced features and functionality. PostgreSQL has built-in support for parallelism that allows it to process queries faster by splitting them into smaller parts that can be executed in parallel. MySQL, on the other hand, has limited support for parallelism and relies heavily on third-party tools to achieve parallel processing.

One of the key features that sets PostgreSQL apart is its ability to execute queries in parallel across multiple CPU cores. This means that PostgreSQL can split a single query into multiple sub-queries, which can be processed simultaneously on different CPU cores, resulting in faster query processing times. In addition, PostgreSQL's query planner is capable of identifying which parts of a query can be executed in parallel and which parts need to be executed sequentially, making it more efficient than MySQL in terms of query processing time.

MySQL does have some support for parallel processing, but it is limited to certain operations, such as index creation and data import/export. For more complex queries, MySQL relies on third-party tools, such as Apache Spark, to achieve parallelism. While these tools can help MySQL achieve some degree of parallel processing, they are often more difficult to set up and use than PostgreSQL's built-in parallel processing capabilities.

In summary, if you're looking for a database that can handle large, complex queries with ease, and that has robust support for parallel processing, PostgreSQL is the clear winner over MySQL.