Deepnote vs Hex: pricing, features and which to choose

Deepnote is a hosted notebook workspace for analysts, data scientists, and teams, made by Deepnote. It supports Python, SQL, charts, databases, machine learning, collaboration, scheduled runs, and published dashboards or data apps. The company describes it as a drop-in Jupyter replacement with managed cloud compute. Its public beta launched in October 2020, followed by general availability in May 2022. Deepnote’s GitHub repository says more than 500,000 data professionals use the product and identifies Estée Lauder, SoundCloud, Statsig, and Gusto as customers. The current open-source repository was created in September 2025 under the Apache 2.0 license. That local project supports notebook editing and related tooling, but it remains separate from Deepnote Cloud and does not represent the complete hosted service.

A typical Deepnote project combines Python, SQL, text, chart, visualization, and input blocks, with reactive execution rerunning dependent blocks when inputs change. Users connect services such as BigQuery, Snowflake, and PostgreSQL, query live data without copying it locally, and pass SQL results into Python within one notebook. Deepnote AI can generate, explain, edit, and debug code. Deepnote Agent can create and run blocks, inspect outputs, and handle multistep notebook tasks. Teams can share projects, schedule notebook runs, and publish notebooks as dashboards or interactive data apps with inputs. The REST API manages projects, notebooks, and workflows. Streamlit provides another publishing route. The hosted product supports Jupyter notebooks through its Deepnote kernel, while the separate Apache 2.0 local project supports VS Code, Cursor, and Windsurf.

Deepnote adds hosted projects, managed compute, database connections, browser collaboration, revision history, scheduling, publishing, and AI to the Jupyter notebook model. Hex is more focused on warehouse BI, dashboards, and self-service exploration, whereas Deepnote also supports machine learning, local IDEs, and scheduled workflows. Databricks covers a broader production data platform, so its operational scope exceeds a notebook workspace. Google Colab is a closer lightweight alternative, but Deepnote emphasizes team projects, database access, deployable outputs, and an API for managing notebooks and workflows. Its main limitation is the separation between the Apache 2.0 local project and Deepnote Cloud, which is not a complete self-hosted Cloud equivalent. Usage beyond included Team compute or AI credits can also cost extra. Choose Deepnote if your technical team needs shared Python and SQL notebooks with cloud execution, scheduled runs, and published outputs.

Hex Technologies makes a hosted analytics workspace for data teams and business users who consume their work. The company says it was founded in 2019 and supports more than 2,000 customers globally. Its May 2025 Series C announcement reported more than 1,500 teams and disclosed a $70 million round from Avra, a16z, Amplify, Box Group, Next Legacy, Redpoint, Sequoia, and Snowflake. Hex combines collaborative notebooks, SQL, Python, visual exploration, conversational Threads, Context Studio, and interactive data apps. That combination places it between a notebook, a business intelligence product, and an internal application builder. The hosted format suits organizations that want shared projects, connected warehouse data, and managed administration without operating the analytics service themselves.

A typical Hex workflow starts with a warehouse or another connected data source, followed by a project containing SQL, Python, charts, and markdown cells. Analysts can use Explore and Threads for natural-language questions, while Notebook Agent can help create analysis and visualizations. Context Studio adds semantic models, database descriptions, and workplace rules that shape AI responses. A completed project can become a published app, shared collection, or scheduled workflow with alerts. Hex runs live queries against connected databases, and its security documentation says project data is ephemeral in kernel memory, with configurable caching. REST APIs and integrations for Airflow, Dagster, dbt, Git, and MCP support teams that connect analytics to existing development and orchestration processes.

Hex's main strength is the connection between exploratory code and governed, shareable output. The cost structure requires attention because editor seats, AI credits, warehouse queries, and larger compute profiles can all affect the bill. Tableau is a deeper traditional business intelligence choice for standardized dashboards and broad administration. Mode is closer for SQL-first reporting and notebook analysis. Deepnote is a closer collaborative notebook alternative, with less emphasis on published analytics apps in this comparison. Hex suits teams that want one hosted workflow from warehouse investigation to interactive application and governed natural-language access. Choose Tableau for dashboard administration, Mode for SQL-centered reporting, or Deepnote for notebook-centered collaboration. Hex is intended for data teams, analysts, and business users sharing governed analytics.