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Databases · head to head

MotherDuck vs Sigma Computing

MotherDuck logo

MotherDuck

Databases

Serverless analytics data warehouse built on DuckDB

From
Free
Rated
-
Full reviewWebsite
Sigma Computing logo

Sigma Computing

Spreadsheets

Spreadsheet-style analytics that queries a cloud data warehouse directly with no extract layer

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only MotherDuck has a free tier, so it costs nothing to try first.
  • Each has a real cost: MotherDuck the free Lite plan caps compute at 10 hours per month, which limits it to light or hobbyist workloads.; 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: MotherDuck covers Serverless DuckDB instances, 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 MotherDuck and Sigma Computing actually diverge.

Attributes where MotherDuck and Sigma Computing differ
AttributeMotherDuckSigma Computing
Starting priceFreeOn request
Pricing modelusage-basedquote
Free tierYesNo
Platformsweb, apiWeb
CategoryDatabasesSpreadsheets
Founded2022Unknown

Identical on both: user rating (Not yet rated).

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 MotherDuck

  • Serverless DuckDB instances
  • Cloud storage querying
  • MCP server
  • Dives
  • Flights
  • Read-scaling replicas

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.

MotherDuck

  • Ad-hoc analytics on gigabyte-to-terabyte datasetsnot Sigma Computing
  • Querying data lake files in S3/GCS/Azure without ingestionnot Sigma Computing
  • AI agent data analysis via MCPnot Sigma Computing
  • Scheduled data pipeline transformationsnot Sigma Computing

Sigma Computing

  • A finance or operations team that lives in spreadsheets and needs warehouse-scale data without exporting CSVsnot MotherDuck
  • An organisation that has consolidated on Snowflake or Databricks and wants one governed access layer rather than several desktop toolsnot MotherDuck
  • Planning and scenario work where users need to type assumptions back into governed tables rather than into a local filenot MotherDuck
  • Embedding customer-facing analytics into a product where each tenant must only see their own rowsnot MotherDuck

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

MotherDuck

  • The free Lite plan caps compute at 10 hours per month, which limits it to light or hobbyist workloads.
  • Business plan usage charges on top of the $250/month base can make costs less predictable than flat-rate competitors.
  • There are no academic or non-profit discounts, unlike some competing data platforms.
  • Annual billing requires going through a sales conversation rather than a self-serve toggle.

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

MotherDuck

Free
  • LiteFree
    • Up to 3 internal active users
    • 2 service accounts
    • 10GB free storage
  • Business$250/month
    • Up to 10 internal active users
    • Unlimited service accounts
    • 5 instance types with read-scaling replicas
  • Enterprise$undefined/month
    • Unlimited internal users and service accounts
    • Fixed-cost capacity pricing
    • AWS PrivateLink, IP allowlisting

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 MotherDuck if

  • You need serverless duckdb instances.
  • You want to start without paying.
  • You work on web, api.
  • You also want cloud storage querying.
MotherDuck review

Choose Sigma Computing if

  • You need spreadsheet interface over sql.
  • You also want no extract layer.
Sigma Computing review

Questions people ask

Is MotherDuck or Sigma Computing better?
Neither clearly leads. MotherDuck 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, MotherDuck or Sigma Computing?
MotherDuck has a free tier; the other does not. Paid plans start at Free for MotherDuck and On request for Sigma Computing.
Does MotherDuck or Sigma Computing run on more platforms?
MotherDuck runs on web, api. Sigma Computing runs on Web.
Can I use MotherDuck for free?
Yes. MotherDuck has a free tier, so you can try it without paying. Sigma Computing starts at On request.
What is MotherDuck best used for?
MotherDuck is most often used for ad-hoc analytics on gigabyte-to-terabyte datasets, querying data lake files in s3/gcs/azure without ingestion, ai agent data analysis via mcp, scheduled data pipeline transformations. Of those, ad-hoc analytics on gigabyte-to-terabyte datasets and querying data lake files in s3/gcs/azure without ingestion are not what Sigma Computing is typically brought in for.
What can MotherDuck do that Sigma Computing cannot?
MotherDuck covers Serverless DuckDB instances, Cloud storage querying, MCP server, Dives. Sigma Computing covers Spreadsheet interface over SQL, No extract layer, Input tables and write-back, Workbooks.

Answered from the vendors’ own pages

MotherDuck: What does MotherDuck cost?

The Lite plan is free (up to 3 users, 10GB storage, 10 hours of Pulse compute/month). Business is $250/organization/month plus usage, with Enterprise available at custom fixed-cost pricing.

Source
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.

MotherDuck: Is there a free plan and what are its limits?

Yes, the Lite plan is free for up to 3 internal active users and 2 service accounts, with 10GB of storage and 10 hours of Pulse compute per month.

Source
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.

MotherDuck: How is usage metered?

Compute instances (Pulse, Standard, Jumbo, Mega, Giga) are billed per second at hourly rates from $0.60 to $24.00/hour, storage is $0.04/GB-month, and AI Functions cost $1.00 per AI Unit.

Source
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.

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.

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