Files are data entities uploaded to datasets on Redivis. Files are used to store non-tabular (a.k.a. unstructured) data of any file type. You can view a dataset's files by clicking on the Files tab of any dataset or dataset node in a project.

Inspecting files

You can inspect an individual file by clicking on its name to launch the file viewer. Any file can be downloaded or referenced within a notebook, and many file types can be previewed directly within Redivis, including:

  • 3D models

  • Audio files

  • CIF + PDB files (molecular + protein structures)

  • FITS files (common in astronomy)


  • HDF5

  • HTML

  • Images

  • PDFs

  • Videos

  • Text/code

  • TIFFs

  • ZIPs

  • TEI

If you have a file type that you think should be supported that isn't, please let us know!

You can view example files on the Redivis Demo organization.

Folders and index tables

All files are assigned to a "folder" within the dataset. You can click on the folder name in the right grey bar to filter this dataset's files by the folder they are in.

Each folder has a corresponding index table that is present on the Tables tab of the dataset. These will match the folder name and have a File index label.

In these index tables, each row of the table represents a file in that folder.

Variable nameDescription


A unique, system generated identifier for the file. Use the file_id to reference and download specific file(s) in your analysis.


The name of the file


Size of the file in bytes


Timestamp for when the file was added to this folder


MD5 checksum of the file contents, encoded as a base64 string

Working with files

By representing files within an index table, we can query and subset the files within a project, while joining them with other tabular metadata. In this way, file index tables behave like any other tabular metadata on Redivis.

To do deeper analysis of files, we can load these files in a notebook for further analysis. Consult the documentation for your preferred programming language to learn more:

Working with unstructured data files in Python >

Working with unstructured data files in R >

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