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RAW is a comprehensive platform that accelerates data engineering projects by allowing developers to easily access, integrate, and deliver data services as APIs. The platform includes development tools, testing, CI/CD, hosting and managed operations.

We have compiled a list of sample use cases to better understand how to use RAW in practice. Each of these targets a different application of the platform and together cover the various parts of a data pipeline from acquisition, transformation up to data sharing:

  • Real-time data integration without ETL/ELT pipelines. Learn how to use RAW to build APIs that join and serve data in real-time. We compare with a common-place solution: building a data lake/warehouse then using tools such as DBT or Denodo/MuleSoft. We demonstrate how many such scenarios can instead be accomplished far more quickly and simply in RAW and with access to real-time data instead of waiting for data ingestion or paying for data duplication.
  • Augment your data integration pipeline with real-time data. Learn how to use RAW to augment your existing ETL/ELT infrastructure with real-time data from other data sources. We focus in RAW's capabilities to access and transform complex data and compare with common-place solutions such as FiveTran, DBT or custom Python or Scala code. We demonstrate how these scenarios can be implemented easily in RAW and enable real-time data in your data engineering pipeline.
  • Share data in real-time. Learn how to use RAW to expose data as APIs to other internal or external users and applications. In particular we focus on how to create and share multiple "virtual real-time views" in RAW, without having to create, extend or modify existing data pipelines.

Choose one of the above to get started!

If you have questions/comments, reach out to us directly or leave a message in our discussion forum.