Data Farm

Data Farm is Stanford University's research data exploration, extraction, and analysis tool for datasets.

What to expect

Stanford contracts with Redivis for use of their SaaS platform for storing, distributing, and analyzing data collections. Redivis offers a modern, high-performance web-based interface that enables researchers to work with a wide variety of datasets and data types.

The data farm consists of multiple organization homepages (a.k.a. “data portals”) on the Redivis platform with access to datasets provided by these organizations. Uploaded datasets can be completely private, shared with specific individuals, or made public. Researchers are able to browse available datasets, apply for access, perform analyses, and export data derivatives and final figures.

You can browse the organizations using Redivis at Stanford on our institution homepage, the Stanford Data Farm.

Get started with Redivis

Who is eligible?

Anyone with a SUNet ID is eligible to use Redivis for free. 

Redivis for researchers

Dataset discovery

Redivis allows researchers to easily discover and preview available datasets, including viewing metadata and summary statistics.

Easy access applications

Redivis makes it easy to access restricted data. Researchers can view the access requirements for different datasets and apply for access directly on the platform.

Integrated analysis tools

Researchers can perform analyses using the high performance computational tools built into the Redivis platform. Analyses can be performed in SQL, Python, R, Stata, and SAS, alongside a no-code graphical interface. There are also options to export or download data, as permitted by the data owner and data access rules.

Collaboration and reproducibility

Real-time collaboration is built into Redivis, allowing researchers to easily share their work with collaborators. All data and analyses are automatically version controlled, ensuring reproducibility. Redivis aligns with FAIR data practices and funder data sharing and reproducibility requirements.

Redivis for data administrators 

Upload any dataset

Any data type can be uploaded to Redivis and easily be cleaned, versioned, and securely distributed. Redivis enables you to host extremely large and/or high risk datasets without any infrastructure investment.

Give researchers the tools to work with your data

Redivis gives researchers access to high-performance computing through the tools that they are familiar with (Python, R, Stata, SAS, SQL, and no-code interfaces), and makes it easy for them to share their work with data administrators and other collaborators.

Configure access systems

Redivis allows you as an administrator to easily distribute restricted or high-risk datasets. Grant access to datasets through automatic authentications, custom forms, group status, and direct sharing.

Create reports

Custom reports allow you to better understand data usage and the impact of your datasets.

Types of data that can be uploaded to Redivis

Redivis can be used for any kind of data (tabular, geospatial, free text, images, binary, etc). It is particularly useful for very large and/or high-risk datasets, due to its scalability and advanced access controls.

Redivis in the classroom

The Redivis platform removes the barrier of students configuring a data analysis environment on their own machine, and allows anyone to share their analytical workflows and code with a single click (and appropriate data access). Collaborative workflows make it easy to check work and leave comments on others’ workflows.

The analysis tools on Redivis offer a no-code interface, alongside SQL, Python, R, Stata, and SAS. Extensive documentation and examples facilitate students’ learning and application of data science concepts.

Redivis can host high-risk data

Redivis is designed for hosting high-risk data. It utilizes HIPAA and FedRAMP certified Google Cloud infrastructure, and has undergone thorough and regular security audits (e.g., SOC2 Type 2).

Please contact us to learn more about hosting high-risk data.


For researchers using the Data Farm, there are never any fees required. Anyone can make a free researcher account to apply for access and analyze data, including collaborators from other institutions. Researchers can opt to attach additional paid computational resources onto the standard Redivis notebook when doing resource-intensive research if they choose (e.g., for GPU-intensive workloads).

For organizations, there are fees associated with data storage based on the amount of data uploaded. All organizations are granted a standard amount of free data storage. Beyond this free allotment, organizations will need to pay their own data storage fees (which include unlimited computing).

Questions about the data farm on Redivis?

Contact us to learn more about the Stanford Data Farm.

Last updated June 11, 2024