Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
Collect and extract comments, video metadata and user profiles on Poal.
The Custom Function component allows you to write Python functions to manipulate and transform documents within your pipeline. This flexibility enables you to perform a wide range of tasks, from simple data cleaning to merge documents. Whether you're filtering documents, enriching data, or transforming formats, the Custom Function component empowers you to customize your pipeline to meet your specific needs.
How Datastreamer works
Quickly enrich Open Measures Poal with Cloud Run Functions with a Datstreamer Pipeline.
Enterprise-grade data pipelines begin with flexible data ingestion. Web data—sourced from partners, internal platforms, or the open internet—provides the raw inputs needed for integration and transformation.
Transform your web data at scale with Datastreamer. Whether you're enriching, storing, joining, or filtering, you'll find hundreds of ready-made operations to help you move fast.
Datastreamer transforms how you use web data. Grow your Pipelines without disruption and finally streamline the operational side of your workflow.
Add Datastreamer components to your data stack and explore its full capabilities
