Talend Cloud Pipeline Designer features
Information noteDeprecation: This document was
last updated in March 2024 and its content might not be up to date. For recent
information about feature availability, see Data Integration and Quality Pricing and
Product Terms.
| Feature | Available in... |
|---|---|
| Ability to do data transformations including filter,
flatten/normalize, aggregate, replicate, look up, join, and time
windowing. Ability to standardize, cleanse, and enrich data in the pipeline. |
|
| Extract, transform, and load (ETL) connectors. See the Talend Cloud Apps Connectors Guide. | |
| Ability to design batch and streaming pipelines in the same interface, using the same connectors and graphical components. See Talend Cloud Pipeline Designer concepts. | |
| Live preview of sample data. See Previewing data in a pipeline. | |
| Schema on-read support. See Predefined semantic types. | |
| Easily embed Python code. See Python 3. | |
| Support data formats including: AVRO, JSON, Parquet, Excel, and CSV. See Creating a test dataset. | |
| Quickly evaluate the quality of your datasets with Talend Trust Score. See Talend Trust Score. | |
| Store data in shared, common dataset repository across all Talend products. See Dataset detailed view. | |
| Write into Talend Data Stewardship campaigns. See Talend Cloud Data Stewardship campaigns. |