# Hex

Hex is a collaborative data workspace and notebook platform for teams to explore, analyze, and share data interactively. It combines SQL, Python, and visualizations in a cloud-based environment.

Hex is a cloud-based collaborative data workspace and notebook platform designed for data scientists, analysts, and engineers. It provides an interactive environment where users can combine SQL and Python code with visualizations and narrative text to explore data, build analyses, and share results as interactive data apps or reports. The platform emphasizes team collaboration, reproducibility, and the ability to move from data exploration to production-ready outputs without switching between multiple tools.

Founded in 2019 by Barry McCardel, Yifat Dolev, and Glen Takahashi, Hex emerged from the founders' experience at Palantir Technologies, where they built data integration and analysis tools for large enterprises. The company is headquartered in San Francisco, California, and has positioned itself within the broader ecosystem of modern data tools, competing with platforms like Jupyter Notebooks, Observable, and Deepnote. Hex raised significant venture funding, including a $52 million Series B round in 2022 led by Andreessen Horowitz, bringing its total funding to over $80 million.

## Core Features

Hex's primary offering is its web-based notebook interface, which supports both SQL and Python cells within the same document. Users can write queries against various data sources, including [Amazon Web Services](https://www.wikiprompt.org/wiki/amazon-web-services) (AWS) S3, [Google Cloud](https://www.wikiprompt.org/wiki/google-cloud) storage, and [Microsoft Azure](https://www.wikiprompt.org/wiki/azure) Blob, as well as databases like Snowflake, BigQuery, and Postgres. The platform includes a built-in data catalog and schema browser, allowing users to discover and connect to datasets with minimal setup.

A distinguishing feature is the ability to create interactive data apps directly from notebooks. Users can add parameters, dropdowns, and sliders that dynamically filter or transform data, and then publish these as shareable web applications. This bridges the gap between static analysis and full-fledged software development, enabling non-engineers to interact with complex models. Hex also supports scheduled runs, allowing notebooks to execute on a timer and send results to email or Slack.

## Collaboration and Sharing

Hex is built around real-time collaboration, similar to [Google Docs](https://www.wikiprompt.org/wiki/google-cloud) or Figma. Multiple users can edit the same notebook simultaneously, with presence indicators and version history. Comments can be attached to specific cells or outputs, facilitating discussion within the context of the analysis. The platform also includes role-based access controls, allowing organizations to manage who can view, edit, or publish notebooks.

Sharing is a core focus: notebooks can be published as read-only reports or as interactive apps with a URL, without requiring recipients to have a Hex account. This lowers the barrier for stakeholders to explore data themselves. Hex also integrates with Slack and Microsoft Teams for notifications and with GitHub for version control, enabling teams to track changes to analysis code over time.

## Technology and Architecture

Under the hood, Hex runs on a serverless architecture, leveraging [AWS](https://www.wikiprompt.org/wiki/amazon-web-services) and [Google Cloud](https://www.wikiprompt.org/wiki/google-cloud) for compute and storage. Each notebook is executed in an isolated container, with resources scaled automatically based on workload. The platform supports a wide range of Python libraries, including pandas, NumPy, scikit-learn, and [TensorFlow](https://www.wikiprompt.org/wiki/tensorflow), as well as SQL dialects for major databases. This flexibility allows users to perform [machine learning](https://www.wikiprompt.org/wiki/machine-learning) tasks, such as training [neural networks](https://www.wikiprompt.org/wiki/neural-network) or running [large language models](https://www.wikiprompt.org/wiki/large-language-model) for text analysis, directly within the notebook environment.

Hex also includes a feature called "Magic SQL," which allows Python variables to be referenced inside SQL queries, and vice versa, enabling seamless data flow between languages. The platform's compute engine is optimized for interactive query performance, using caching and incremental execution to speed up repeated analyses.

## Use Cases and Applications

Organizations use Hex for a variety of tasks, including data analysis, business intelligence, and data science workflows. Common use cases include customer segmentation, financial modeling, operational dashboards, and A/B testing analysis. For example, a growth team might use Hex to connect to their product analytics database, write SQL to extract user cohorts, then use Python to run a regression analysis and visualize the results in an interactive chart that stakeholders can filter by date or region.

The platform is also used for data engineering tasks, such as data cleaning and transformation, and for data governance, as it provides audit logs and lineage tracking. Hex's ability to publish interactive apps has made it popular for internal tooling, such as self-serve reporting portals or model monitoring dashboards, where users can input parameters and see updated outputs in real time.

## Market Position and Future

Hex competes in the growing market for collaborative data notebooks, which also includes Jupyter-based solutions, [Databricks](https://www.wikiprompt.org/wiki/databricks) notebooks, and Observable. Its differentiation lies in its focus on end-to-end workflows, from data connection to interactive app deployment, and its emphasis on non-technical users through a polished user interface. As of 2024, Hex continues to expand its feature set, including enhanced support for [generative AI](https://www.wikiprompt.org/wiki/generative-ai) assistants that can help write SQL or Python code, and deeper integrations with [OpenAI](https://www.wikiprompt.org/wiki/openai) and [Anthropic](https://www.wikiprompt.org/wiki/anthropic) models for natural language queries.

The company has grown its customer base to include mid-market and enterprise clients across technology, finance, and healthcare sectors. With the rise of [artificial intelligence](https://www.wikiprompt.org/wiki/artificial-intelligence) and the need for rapid data-driven decision-making, Hex is well-positioned to serve as a central hub for data teams, though it faces competition from larger cloud providers offering similar notebook services within their ecosystems.

## See Also

- Data analysis
- Python programming
- SQL
- Collaborative software

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Source: https://www.wikiprompt.org/wiki/hex
License: CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/)
Last updated: 2026-09-12T22:22:04.283276+00:00