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Database partitioning is typically used as a technique for configuring a database in order to speed up queries.
Given that the objective is to ensure that your queries run faster, there are a couple of approaches you could use, whilst at the same time preserving the MySQL interface for your application:
a) Load your data into an Aurora MySQL database (without database partitioning) and try running bench-mark tests. Amazon Aurora database engine is designed to be wire-compatible with MySQL 5.6 and 5.7 using the InnoDB storage engine. I have seen quotes that in some cases Aurora can be 5 times faster than on-premises MySQL. It is possible that you will find you get the performance you need from Aurora, without having to resort to database partitioning. Have a look at https://aws.amazon.com/rds/aurora/getting-started/ Don't forget that you could just terminate the benchmark database once you have completed your tests, one of the benefits of using AWS is that you only need to pay for what you use.
b) see if turning on Aurora MySQL parallel query will improve your performance. Parallel Query can be enabled and disabled dynamically at both the global and session level using the aurora_pq parameter. Have a look at https://aws.amazon.com/rds/aurora/faqs/
c) if you are using lots of reads in your application, compared with writes, try introducing Aurora read replicas. https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/Aurora.Replication.html
It might also be worth reviewing the following best practices: https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/AuroraMySQL.BestPractices.html
Hope this helps
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