Alooma supports Python code for customizing transformations, but Etlepa lets analysts and data scientists create production-ready ETL pipelines using an intuitive UI, without the need to write and maintain python code or open engineering support tickets.
Etleap monitors and automatically resolves common pipeline issues such as schema changes that would otherwise break data pipelines and require code troubleshooting.
Made for AWS
Etleap was tailor-made for AWS to provide a seamless integration with high performance, low compute costs, and low latency. Create a Redshift data warehouse or S3 data lake with a click.
Receive priority operational and engineering support from ETL and AWS experts to help build and scale your data infrastructure, regardless of your size.
Designed for the Enterprise
Etleap and Alooma both integrate with cloud applications, databases, and file storages, but Etleap also integrates with complex ERP systems to bring enterprise data into a cloud data warehouse or data lake.
Set custom transformations with an interactive data wrangler, with SQL modeling (post-load transformation), or with custom code in five supported languages. Have data in a standardized and consistent format by the time it’s in the warehouse or data lake.