Choose by who writes the analysis on your team. Analysts working in SQL suit a BI platform, data scientists in Python suit a notebook or app framework, and business users who ask in plain language suit an AI analytics tool. Check who owns a product before you move a team onto it.
Ownership news is a good reason to pause before a migration. One of the tools on this list now says on its own homepage that it's being acquired by ThoughtSpot, and that's exactly the kind of change that can reshape a roadmap. If your data team uses Hex (hex.tech) for notebooks, SQL and shared data apps and you're weighing a move, here are nine alternatives in no particular order.
Two checks before you migrate
First, ownership. The homepage of Mode, a BI platform for SQL, R and Python, now says ThoughtSpot is acquiring it. That isn't a reason to rule it out, but it's a reason to ask the vendor where the product is going before you rebuild a team's reports in it. Do the same for every tool here: who owns it, how it's funded, and whether it's open source with a community behind it.
Second, fit. This list mixes very different things on purpose, because people searching for alternatives to Hex (hex.tech) come from different starting points. Some want a full BI platform. Some want BI written as code. Some want a better Python notebook. Decide which of those you are before you shortlist.
Who builds the analysis
Analysts in SQL: BI platforms
Sigma and Omni put governed warehouse data in front of analysts and business users, with chat, spreadsheets or questions in plain language on top. Rill adds an agent that explains why a number changed. These suit companies where many people need answers, not just the data team.
Engineers who like code: BI as code and open source
Lightdash builds on dbt so metrics live in one place, and the SQL-and-markdown option in the table below lets analysts write reports like documents. Both are open source, which matters to teams who want control over hosting and version history.
Data scientists in Python: notebooks and app frameworks
Deepnote is the closest in spirit to a shared data notebook, with Python and SQL side by side. Streamlit turns Python scripts into interactive apps, and the reactive open-source notebook in the list stores work in Git-friendly files. These suit teams whose analysis starts in code.
Nine data tools side by side
| Tool | Category | Good for |
|---|---|---|
| Deepnote | Collaborative data notebook | Python and SQL exploration shared with a team |
| Evidence | Open-source BI as code | Reports written in SQL and markdown |
| Lightdash | Open-source BI on dbt | Metrics defined once in dbt |
| marimo | Open-source Python notebook | Reactive notebooks stored in Git-friendly files |
| Mode | Collaborative BI platform | SQL, R and Python next to visual analytics |
| Omni | AI analytics platform | Letting anyone ask questions of governed data |
| Rill | BI with an AI agent | Explaining why a number changed |
| Sigma | Warehouse BI and apps | Spreadsheet-style analysis on warehouse data |
| Streamlit | Open-source Python app framework | Turning Python scripts into data apps |
The full list, alphabetically
In no particular order beyond A to Z. Each line reflects the vendor's own description.
Deepnote
Best for: Teams exploring data in Python and SQL and sharing what they find; the vendor calls it one workspace from exploration through to data apps.
Evidence
Best for: Analysts who'd rather write reports than drag charts: open-source BI as code in SQL and markdown, which the vendor says builds polished data products.
Lightdash
Best for: dbt users who want metrics defined once; the vendor describes open-source, AI-first BI that connects to dbt for modern data teams.
marimo
Best for: Python users wanting a reactive, open-source notebook stored in Git-friendly files, with SQL support, that can also run as a script or an app.
Mode
Best for: Mixed teams working in SQL, R, Python and visual analytics together, in what the vendor calls the central hub for an organisation's analysis.
Omni
Best for: Companies that want anyone to ask questions of governed data and get answers, which the vendor says makes that data a source of truth for AI.
Rill
Best for: Explaining why a number moved: the vendor's AI agent runs queries to explain changes, which it describes as agentic analytics beyond dashboards.
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Sigma
Best for: Business users building dashboards, apps and agents on warehouse data through chat, a spreadsheet, SQL or Python, with governance inherited at the source, per the vendor.
Streamlit
Best for: Python developers turning scripts into interactive data apps with an open-source framework; the vendor says it takes only a few lines of code.
My advice for data teams
Don't migrate everything at once. Pick one live project that matters, one that uses your real warehouse, your real SQL and at least one shared app or dashboard, and rebuild it in your two strongest candidates. Ask the people who'll use it every day to judge, not just the person who set it up.
Then think about the long term. Open-source tools give you more control and an exit route, but someone on your team has to own the setup. Hosted platforms take that load off you, but you're tied to the vendor's direction, which is why ownership is worth checking. Version control matters too: if your analysis lives in Git, code-first tools will feel natural, and if it doesn't, a platform with a friendly interface will win adoption faster. For more ideas, see my list of Metabase alternatives and my guide to business intelligence tools.
Do you make BI, analytics or data notebook software? Tool makers can ask to be considered for a featured place on this list.
Want your tool on this list? Featured spots and reviews here are paid partnerships. Here's how to partner with me.
Frequently asked questions
What's the difference between a BI platform and a data notebook?
A BI platform is built for dashboards, governed metrics and sharing answers across a business. A data notebook is built for exploration in code, usually Python and SQL, and suits analysts and data scientists.
What does BI as code mean?
You define reports and metrics in code, such as SQL and markdown, and keep them in version control. It suits teams who already work in Git and like reviewing changes.
Should we pick an open-source tool?
It gives you control over hosting and a route out if the company changes direction. In exchange, someone on your team has to run and update it.
How long does a migration take?
It depends on how many reports and apps you have. Rebuild one live project first, then plan the rest once you know how long that took.
Why does ownership of a tool matter?
Acquisitions can change roadmaps, plans and integrations. Ask the vendor where the product is heading before you move a team's work onto it.
Can business users work in these tools without SQL?
Some offer chat, spreadsheet-style views or questions in plain language. Others expect SQL or Python, so check who'll be using it day to day.
