AWS RDS, Amazon Athena, Amazon QuickSight and Amazon Redshift

Amazon Athena is well suited for interactive analytics and exploration of data in your data lake or any data source through an extensible connector framework without worrying about ingesting or processing data. Amazon Athena is built on open-source engines and frameworks such as Spark, Presto, and Apache Iceberg, giving customers the flexibility to use Python or SQL or work on open data formats. If customers want to do interactive analytics using open-source frameworks and data formats, Amazon Athena is a great place to start.

Amazon Redshift is a fully managed data warehouse. With its Massively Parallel Processing (MPP) architecture that separates storage and compute and machine learning led automatic optimization capabilities, a data warehouse like Amazon Redshift, whether it's serverless or provisioned, is a great choice for customers that need the best price performance at any scale for complex BI and analytics workloads. Using Amazon Redshift, you can also directly query data in open formats (such as Parquet or ORC) in the Amazon S3 data lake, or query data in operational databases, such as Amazon Aurora and Amazon RDS PostgreSQL and MySQL.

Amazon QuickSight is a cloud-scale business intelligence (BI) service that you can use to deliver easy-to-understand insights to the people who you work with, wherever they are. Amazon QuickSight connects to your data in the cloud and combines data from many different sources.

Here is a document on the Modern Data architecture with AWS which gives an idea on how the purpose built services can be used together. [https://aws.amazon.com/big-data/datalakes-and-analytics/modern-data-architecture/]