AWS S3 Tables is a new service that simplifies the usage of Iceberg open table format by providing automatic setup and maintenance, including built-in table maintenance and optimization. This service mainly relies on Apache Spark, which requires complex configuration and a Java-based engine. Bodo, an open-source high-performance compute engine for Python data processing, addresses this challenge by offering simple S3 Tables usage in both Python and SQL, simplifying the read and write of large tables with high performance and efficiency. Bodo enables efficient querying and processing of S3 Tables without the need for complex infrastructure or data movement, allowing users to perform analytical queries, aggregations, and transformations on S3 Tables using familiar Pandas APIs. To use S3 Tables, users need active AWS credentials and the necessary dependencies installed and upgraded, as well as the AmazonS3TablesFullAccess policy attached to their credentials. Bodo provides a simple way to write dataframes with its `to_sql` method and read tables into dataframes using the Pandas `read_sql_table` function. This feature is available in Bodo pip and Conda releases starting from 2025.1, and users can try it out by installing Bodo with pip or Conda.