Deepnote

Deepnote is a cloud-based data notebook built for teams. It combines Python, SQL, and R in a single environment, adds AI that understands your codebase and data stack, and makes real-time collaboration as straightforward as sharing a link. It's now fully open-source under Apache 2.0, making it a credible alternative to tools like Hex or hosted Jupyter setups.

The AI layer goes beyond code completion. Deepnote's assistant is aware of your schema, your existing code, and your business context. It can generate queries, explain results, debug errors, and surface drivers behind a metric shift. You describe what you want to find; it writes the analysis. For teams without dedicated data engineers, that matters.

Beyond notebooks, Deepnote covers a surprising range of output types:

• Dashboards and data apps built directly from notebook outputs, with custom layouts and input controls
• Scheduled notebooks that run hourly, daily, or on any cadence you set
• API deployment so models or queries can be served as live endpoints
• GPU compute for ML workloads, selectable from the environment settings
• Data agents that can plan, query, train, and publish results autonomously

SQL is a first-class citizen here, not an afterthought. You can query warehouses directly in SQL blocks, use dbt metadata and Jinja templating, and mix SQL and Python in the same notebook. Connections to Snowflake, BigQuery, Spark, and other major sources are built in. For fans, the AI layer can write the SQL for you.