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What is Hex?

Hex (Hex Technologies, headquartered in San Francisco) helps people use data by building a collaborative, shareable analytics workspace. The Hex solution helps users empower users to ask new questions and share their findings in one product without any friction.

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Recent Reviews

TrustRadius Insights

Hex is a versatile tool that has been leveraged by users to tackle various data analysis tasks. With the ability to easily pull data from …
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per month per Author/Admin




Entry-level set up fee?

  • No setup fee
For the latest information on pricing, visit


  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

Starting price (does not include set up fee)

  • $75 per month per Author/Admin
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Product Demos

Hex Demo

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Product Details

What is Hex?

Hex Technical Details

Deployment TypesSoftware as a Service (SaaS), Cloud, or Web-Based
Operating SystemsUnspecified
Mobile ApplicationNo
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Reviews and Ratings


Community Insights

TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!

Hex is a versatile tool that has been leveraged by users to tackle various data analysis tasks. With the ability to easily pull data from multiple databases and perform quick analyses using Python notebooks, Hex offers a convenient computing platform for Data Science and Machine Learning. The software's fantastic visualizations, including the creation of heatmaps from custom geoJSON files, have impressed users and allowed them to gain valuable insights from their data.

One of the key problems solved by Hex is the integration of SQL and Python for data analysis. Users can seamlessly switch between these two languages, taking advantage of dataframe querying and enabling engineers and business analysts to come up with quick solutions to their business problems. Additionally, Hex solves the challenge of creating interactive BI tools by offering easy-to-use Python tools for data analysts. This empowers them to build more complex dashboards and conduct detailed exploratory analyses.

Another prominent use case for Hex is its role as an app builder for interactive data products. It enables non-technical stakeholders to create code-free analysis dashboards and automated workflows. By bridging the gap between traditional BI tools and Google Colab, Hex makes it easy to build advanced analyses with Python and share them with the team. Furthermore, organizations appreciate Hex's ability to automate data manipulation and interactions with end-users, saving valuable time in generating results across various platforms.

Hex has found success in supporting deep-dive analyses, ad-hoc reporting, dashboard creation, and handling one-off analytical requests. Its flexibility lends itself well to scenario modeling and building simple internal apps. Additionally, users find value in utilizing Hex for exploratory data analysis, migrating dashboards from other tools, and creating analytical tools for internal teams.

Overall, Hex has proven to be a powerful asset for users across different industries. It facilitates collaboration among analytics teams, increases transparency in delivering insights, provides an enhanced experience for stakeholders, and contributes to building industry expertise through written reports, statistical analyses records, and dashboards.


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Score 10 out of 10
Vetted Review
Verified User
We use as a tool for data scientists and analysts to write reports, build dashboards, and keep records of statistical analyses. We're building a body of product knowledge to inform decisions and contribute to building industry expertise at the company.
  • Powerful interactive notebook environment
  • Balances the need of code and non-code users
  • Provides free and easy sharing to viewers of analyses across the company
  • Responds promptly to support requests and needs
  • High quality native charting capabilities
  • Limited support for R notebooks
  • Limited sharing outside of the app (e.g., no slack integration)
  • Some Python knowledge needed for highest levels of aggregations is an excellent tool for a product intelligence or product analytics team that wants to enable widespread use of available data for decision-making. It requires some SQL experience in many cases but makes it possible to go far without complex querying skills.
  • Increased visibility into analyses with free membership tier across company
  • Increased capacity for self-service analytics among R&D stakeholders (e.g., product managers)
  • Improved productivity of data science team with ease of use is the easiest to use, most enjoyable experience, most powerful environment, and most cost scalable of all the above.
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