We believe that it is critical for the success of a software product to be clear about its positioning. We built DataCater to make operational streaming data pipelines accessible to data and developer teams.
Please see the following sections to learn about the use cases that DataCater excels at and the use cases that DataCater has not been built for.
- Making real-time ETL pipelines accessible to data and developer teams
- Supporting Python-based transforms for ETL and streaming use cases
- Applying cloud-native principles to data development
- Declarative pipeline definition, which enables DataOps and Continuous Delivery
- Interactive development of ETL pipelines with minimal time to production
- EL or ELT pipelines with post-load transforms
- Analytics use cases that make use of aggregations or multiple joins
- Traditional batch processing