Lake Formation table read performance

In order to optimize performance, it is typically necessary to analyze the specific details of the data and query on a case-by-case basis. Identifying the performance bottlenecks is crucial before providing any optimization recommendations. Each scenario may have unique factors that contribute to performance issues, and a thorough assessment is necessary to determine the most effective optimization strategies. To better answer your question, we require details that are non-public information. Please open a support case with AWS using the following link.

Based on the information provided, it could make sense that the Athena query took longer time than a local query for smaller datasets. When querying through Athena, the query execution occurs remotely, involving additional steps and API calls. Additionally, Athena is designed to optimize performance for large-scale data scenarios by utilizing distributed computing, which introduces additional overhead compared to local processing on a single node. This overhead can become much more noticeable when working with smaller datasets.