Spreadsheets · head to head
Quadratic vs Sigma Computing
Quadratic
Spreadsheets
Infinite-canvas spreadsheet that runs Python, SQL and formulas in the same grid
- From
- Free
- Rated
- -
Sigma Computing
Spreadsheets
Spreadsheet-style analytics that queries a cloud data warehouse directly with no extract layer
- From
- On request
- Rated
- -
The short version
- Only Quadratic has a free tier, so it costs nothing to try first.
- Each has a real cost: Quadratic aI usage is metered as a dollar allowance rather than a flat entitlement, so a team that adopts the agent enthusiastically will exhaust 20 USD per user per month quickly and the true cost per seat becomes unpredictable.; Sigma Computing every user interaction is a live warehouse query, so compute costs rise with adoption and land on the warehouse invoice rather than the BI line item, which routinely surprises the team that approved the purchase.
- They diverge on capability: Quadratic covers Multi-language cells, Sigma Computing covers Spreadsheet interface over SQL.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Quadratic and Sigma Computing actually diverge.
| Attribute | Quadratic | Sigma Computing |
|---|---|---|
| Starting price | Free | On request |
| Pricing model | Per user per month | quote |
| Free tier | Yes | No |
| Platforms | Web, macOS, Windows, Linux | Web |
Identical on both: user rating (Not yet rated), category (Spreadsheets).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in Quadratic
- Multi-language cells
- Infinite canvas
- Direct database connections
- AI agent in the sheet
- WebAssembly engine
- Python package support
Only in Sigma Computing
- Spreadsheet interface over SQL
- No extract layer
- Input tables and write-back
- Workbooks
- Embedded analytics
- Version control and dbt awareness
What people use each for
The jobs each tool is most often brought in to do.
Quadratic
- An analyst who wants a SQL result, a Python transformation and a set of manual assumptions visible in one file instead of three toolsnot Sigma Computing
- Ad hoc modelling where part of the logic is genuinely code and part is a judgement call typed into a cellnot Sigma Computing
- Sharing a reproducible analysis with a colleague who will only ever open a spreadsheet, not a notebooknot Sigma Computing
- Prototyping a data pull against a warehouse before committing it to a scheduled pipelinenot Sigma Computing
Sigma Computing
- A finance or operations team that lives in spreadsheets and needs warehouse-scale data without exporting CSVsnot Quadratic
- An organisation that has consolidated on Snowflake or Databricks and wants one governed access layer rather than several desktop toolsnot Quadratic
- Planning and scenario work where users need to type assumptions back into governed tables rather than into a local filenot Quadratic
- Embedding customer-facing analytics into a product where each tenant must only see their own rowsnot Quadratic
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Quadratic
- AI usage is metered as a dollar allowance rather than a flat entitlement, so a team that adopts the agent enthusiastically will exhaust 20 USD per user per month quickly and the true cost per seat becomes unpredictable.
- Self-hosting is available only on the Enterprise plan, so an organisation that cannot send data to the vendor cloud has to enter a sales negotiation rather than run a container.
- Excel and Google Sheets compatibility is partial, so files with heavy conditional formatting, pivot tables or macros do not survive a round trip and have to be rebuilt.
- The product is young and the connector list is short, covering the main relational databases and two warehouses, so anything else has to be reached through Python code you write and maintain yourself.
- There is no real mobile editing experience, which matters more than it sounds for a spreadsheet because approvals and quick checks routinely happen on a phone.
Sigma Computing
- Every user interaction is a live warehouse query, so compute costs rise with adoption and land on the warehouse invoice rather than the BI line item, which routinely surprises the team that approved the purchase.
- It cannot work without a supported cloud data warehouse, so an organisation running analytics on an on-premises database or a plain application database has nothing to connect to.
- Pricing is not published and seats are differentiated by capability, so budgeting requires a sales cycle and a headcount forecast before you can compare it with a tool you could simply buy.
- Performance is only as good as the warehouse behind it, which means slow or badly modelled tables surface as a slow interface and the fix is a data engineering project, not a Sigma setting.
- Statistical and scientific visualisation is limited compared with dedicated tools, so anything beyond standard business charting has to be done elsewhere and brought back in.
Pricing, plan by plan
Quadratic
Free- PersonalFree
- Limited AI usage
- Limited files and connections
- Limited sharing
- Pro$18/month
- Billed annually
- 20 USD of AI credits per month
- Unlimited files
- Business$36/month
- Billed annually
- 40 USD of AI credits per month
- Advanced permissions
- Enterprise$undefined/year
- Quoted
- Self-hosting option
- Custom AI usage
Sigma Computing
On request- Sigma Computing$undefined/year
- Quoted per organisation
- Seat types are differentiated by whether a user views, explores or authors
- Warehouse compute is billed separately by your cloud data warehouse vendor
Which should you pick?
Choose Quadratic if
- You need multi-language cells.
- You want to start without paying.
- You work on Web, macOS, Windows, Linux.
- You also want infinite canvas.
Choose Sigma Computing if
- You need spreadsheet interface over sql.
- You also want no extract layer.
Questions people ask
- Is Quadratic or Sigma Computing better?
- Neither clearly leads. Quadratic starts at Free and Sigma Computing at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Quadratic or Sigma Computing?
- Quadratic has a free tier; the other does not. Paid plans start at Free for Quadratic and On request for Sigma Computing.
- Does Quadratic or Sigma Computing run on more platforms?
- Quadratic runs on Web, macOS, Windows, Linux. Sigma Computing runs on Web.
- Can I use Quadratic for free?
- Yes. Quadratic has a free tier, so you can try it without paying. Sigma Computing starts at On request.
- What is Quadratic best used for?
- Quadratic is most often used for an analyst who wants a sql result, a python transformation and a set of manual assumptions visible in one file instead of three tools, ad hoc modelling where part of the logic is genuinely code and part is a judgement call typed into a cell, sharing a reproducible analysis with a colleague who will only ever open a spreadsheet, not a notebook, prototyping a data pull against a warehouse before committing it to a scheduled pipeline. Of those, an analyst who wants a sql result, a python transformation and a set of manual assumptions visible in one file instead of three tools and ad hoc modelling where part of the logic is genuinely code and part is a judgement call typed into a cell are not what Sigma Computing is typically brought in for.
- What can Quadratic do that Sigma Computing cannot?
- Quadratic covers Multi-language cells, Infinite canvas, Direct database connections, AI agent in the sheet. Sigma Computing covers Spreadsheet interface over SQL, No extract layer, Input tables and write-back, Workbooks.
Answered from the vendors’ own pages
Quadratic: Do I need to know Python to use it?
No, formulas work on their own, but the reason to choose Quadratic over Google Sheets is the code cells, so a team with no Python will not get the value.
Sigma Computing: Does Sigma store a copy of my data?
No. Queries are executed on your warehouse and results are returned for display, which is why there is no extract refresh to manage.
Quadratic: What happens when the AI credits run out?
Prompting stops until the next monthly reset or until you move up a plan; the spreadsheet itself keeps working normally.
Sigma Computing: What does it actually cost?
The vendor does not publish prices. Expect an annual contract priced by seat type, plus a warehouse compute increase you should model separately.
Quadratic: Can it replace a BI tool?
Not for scheduled distribution or governed metrics. It is for exploratory work by one person or a small team, not for dashboards a hundred people read.
Sigma Computing: Can business users break the warehouse?
They can run expensive queries. Warehouse sizing, query limits and materialised tables are the controls, and they need configuring before a wide rollout.
Quadratic: Is my database query sent to the vendor?
Connections run through the vendor service on all plans except Enterprise self-hosting, which is the option to take if that is unacceptable.
Sigma Computing: Is it a replacement for a modelling layer like dbt?
No. Sigma works best on top of modelled tables and is usually deployed alongside dbt rather than instead of it.
Related pages
More on Sigma Computing
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