ETL for API Data
Ascend Use Case
ETL for API
Out-of-the-box connectors are great… when they exist and are maintained by the vendor for your data source. When they don’t exist, you’re stuck with the tedious task of building and maintaining an API connector codebase and deployment end-to-end. In contrast, the custom connector framework on Ascend allows you to focus just on the parts that you need from the API, such as fetching, filtering, and transforming. Ascend automates the processing, infrastructure, and maintenance of all the corner cases of API operation: parsing, scheduling, retry/error handling, and loading the data into pipelines as well as onto its end destination (data warehouse, blob store, etc).
How it Works
- Ingest raw data from any API by specifying your data source(s) via our no-code UI, low-code YAML spec, or full-code API & SDKs
- Unify and join your API data with other datasets from your data lake, warehouse, and elsewhere with simple transforms in SQL, Python, Java, or Scala
- Write the resulting data directly to your favorite database, warehouse, blob store, and more.
- Ascend handles the rest — orchestrating runtimes, handling retries/errors, managing parallel jobs, and persisting copies of your data.