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Storing and working with data in the cloud with Redivis: Start

This guide describes the data hosting and sharing platform, Redivis, and CMU Libraries' Redivis trial.

About CMU's Redivis Trial

CMU Libraries is committed to providing researchers with access to Redivis from January 2023 to August 2025. To gain access to the platform, please contact Kristen Scotti ( or Melanie Gainey (

Until August 2025, research groups can put up to 1TB/dataset on the platform for free. Datasets exceeding 1TB will be allowed on a case-by-case basis. Early adopters can take advantage of a high level of customized one-on-one support from Redivis. 

We will gauge campus interest in the platform and further commitment to it over the next couple of years but your data will not vanish in August 2025. You will have options for migrating data or purchasing an individual subscription at that time if we can no longer support that platform.

We welcome and appreciate any feedback you might have, as it helps us make informed decisions about allocating Libraries' budgets to significant resources like this one. This is a platform we're excited about and we encourage you to use and share it with your colleagues.

What is Redivis?

Redivis is a data hosting and sharing platform. It can be used to host datasets for a variety of scenarios including:


  • restricted data sets (i.e. HIPAA and GDPR compliant)
  • data sets that you want to share with collaborators before publication
  • large data sets (greater than 1TB)
  • manipulating tabular data and querying billions of records in seconds with both a GUI and programmatic interface
  • Python, R, or Stata analysis in the cloud with a Jupyter Notebook integration 
  • storing all of a research group's datasets in one place for easy access


3 min Demo of Redivis


Redivis Town Hall Demo


1 hr Demo of Redivis


How is this different from KiltHub?

KiltHub is our institutional repository, built on the Figshare platform. KiltHub is used to archive finished research products for public access, including datasets up to 1TB. 

Unlike KiltHub, Redivis works particularly well for datasets that need to be queried or are still in the collection and analysis phases of research, have specific access permissions, or are larger than 1TB. 

Open Science Postdoctoral Associate

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Kristen Scotti
4416 Sorrells Library
Carnegie Mellon University Libraries
Wean Hall
Hamerschlag Dr
Pittsburgh, PA 15213

Librarian for Biological Sciences, Computational Biology, Biomedical Engineering, and Neuroscience

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Melanie Gainey
Mellon Library
4th Floor Mellon Institute