Athena federated query to Timestream slow

Rearranging the tables in the join to better align with the WHERE clause can often result in a more efficient query plan, significantly reducing the runtime. Using Athena's EXPLAIN feature can help you identify inefficiencies in your query's execution plan. For example, making sure the join operations are performed in the correct order can have a substantial impact on performance. A suboptimal join order may result in unnecessary data processing and longer execution times.

https://aws.amazon.com/blogs/big-data/optimize-federated-query-performance-using-explain-and-explain-analyze-in-amazon-athena/

Additional metadata from AWS Glue Data Catalog may be used to optimize queries; AWS Glue database and table names must match those in Timestream; lowercase names are preferred for optimal performance; mixed case names result in more computationally intensive searches; setting AWS Glue table properties in accordance with Timestream requirements can also improve performance.

https://docs.aws.amazon.com/athena/latest/ug/connectors-timestream.html

https://docs.amazonaws.cn/en_us/athena/latest/ug/connectors-timestream.html

Appreciate the response. No joins are being used here, this is just a straight query to Timestream with a simple predicate that matches the timestream db.

We will integrate into Glue as well and see if that helps improve performance.