Datashim is enabling and accelerating data access for Kubernetes/Openshift workloads in a transparent and declarative way. Opensourced since September of 2019 and is growing to support use-cases related to data access in AI projects. It brings benefits across different entities:

  • Data scientists/engineers: Focus on workload/experiments development and not on configuring/tuning data access
  • Storage Providers: Increase adoption since the framework is extensible without hindering the User Experience
  • Data-oriented Frameworks: Can build capabilities (caching, scheduling) on top of DLF using a declarative way to access/manage data sources

Datashim is a incubation-stage project of the LF AI & Data Foundation.

Contributed by: IBM in January 2021

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