What engines support data ingestion through SageMaker Lakehouse?

Amazon SageMaker Lakehouse supports various engines for data ingestion and querying. While the sources don't explicitly mention DynamoDB and Aurora MySQL as supported engines for SageMaker Lakehouse, they do provide information about some supported engines and data ingestion methods.

SageMaker Lakehouse allows you to query data from Amazon S3 data lakes and Amazon Redshift data warehouses. It supports querying data using engines such as Amazon EMR, AWS Glue, Amazon Redshift, and Apache Spark.

For data ingestion, SageMaker Lakehouse offers flexibility in bringing data into the lakehouse. You can use zero-ETL to bring data from operational databases, streaming services, and applications. Additionally, you can query in-place data via federated query.

While DynamoDB and Aurora MySQL are not specifically mentioned as supported engines for SageMaker Lakehouse in the provided information, it's worth noting that AWS often provides integration between its various services. To get the most up-to-date and accurate information about support for specific databases like DynamoDB and Aurora MySQL with SageMaker Lakehouse, it would be best to check the latest AWS documentation or contact AWS support directly.
Sources
AWS announces Amazon SageMaker Lakehouse - AWS