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Spreadsheets · head to head

Sigma Computing vs Snowplow

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
Snowplow logo

Snowplow

Business Intelligence

Behavioural data pipeline you run in your own cloud, relicensed away from Apache 2.0 in 2024

From
On request
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: 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.; Snowplow the core pipeline was relicensed from Apache 2.0 on 8 January 2024 to the Snowplow Limited Use Licence Agreement and a Confluent-derived community licence, so organisations that adopted it as permissively licensed software must now review their entitlement, buy a licence, or migrate.
  • They diverge on capability: Sigma Computing covers Spreadsheet interface over SQL, Snowplow covers Own-cloud deployment.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Sigma Computing and Snowplow actually diverge.

Attributes where Sigma Computing and Snowplow differ
AttributeSigma ComputingSnowplow
PlatformsWebLinux, Web, Docker
CategorySpreadsheetsBusiness Intelligence

Identical on both: starting price (On request), pricing model (quote), free tier (No), 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 Sigma Computing

  • Spreadsheet interface over SQL
  • No extract layer
  • Input tables and write-back
  • Workbooks
  • Embedded analytics
  • Version control and dbt awareness

Only in Snowplow

  • Own-cloud deployment
  • Schema enforcement
  • Warehouse loading
  • Enrichment
  • Trackers
  • Streaming output
  • Data models
  • Snowplow BDP

What people use each for

The jobs each tool is most often brought in to do.

Sigma Computing

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

Snowplow

  • A data team that needs full-fidelity event data in its own warehouse to build attribution or machine learning features rather than to populate dashboardsnot Sigma Computing
  • A regulated business that cannot send behavioural data to a third-party analytics vendor and must keep collection inside its own cloud accountnot Sigma Computing
  • A product organisation tired of silently malformed events, which wants a schema contract enforced at collection timenot Sigma Computing
  • A company modelling customer behaviour across web, mobile and server events that needs them in one consistent structurenot Sigma Computing

Where each one falls short

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

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.

Snowplow

  • The core pipeline was relicensed from Apache 2.0 on 8 January 2024 to the Snowplow Limited Use Licence Agreement and a Confluent-derived community licence, so organisations that adopted it as permissively licensed software must now review their entitlement, buy a licence, or migrate.
  • You run the pipeline in your own cloud, which means the infrastructure bill, the on-call rota and the upgrade work are yours, and at high event volume that operational cost frequently exceeds what a hosted product would have charged.
  • Schema enforcement is the main benefit and the main friction, because every new event requires a schema to be authored and versioned, and teams without discipline around that end up blocked on their own governance process.
  • There is no analysis layer: Snowplow delivers data to your warehouse and nothing else, so you still need modelling, a BI tool and the people to run them before anyone sees a number.
  • The licence change fractured the community, spawning an Apache 2.0 fork, which means community contributions and third-party tooling are now split across two codebases with uncertain long-term maintenance.

Pricing, plan by plan

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

Snowplow

On request
  • Snowplow BDP$undefined/year
    • Commercial pricing quoted by event volume and deployment
    • Core pipeline components under the Snowplow Limited Use Licence Agreement, not Apache 2.0
    • Trackers, analytics SDKs and Iglu SDKs remain Apache 2.0

Which should you pick?

Choose Sigma Computing if

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

Choose Snowplow if

  • You need own-cloud deployment.
  • You work on Linux, Web, Docker.
  • You also want schema enforcement.
Snowplow review

Questions people ask

Is Sigma Computing or Snowplow better?
Neither clearly leads. Sigma Computing starts at On request and Snowplow at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Sigma Computing or Snowplow?
Sigma Computing starts at On request and Snowplow at On request.
Does Sigma Computing or Snowplow run on more platforms?
Sigma Computing runs on Web. Snowplow runs on Linux, Web, Docker.
What is Sigma Computing best used for?
Sigma Computing is most often used for a finance or operations team that lives in spreadsheets and needs warehouse-scale data without exporting csvs, an organisation that has consolidated on snowflake or databricks and wants one governed access layer rather than several desktop tools, planning and scenario work where users need to type assumptions back into governed tables rather than into a local file, embedding customer-facing analytics into a product where each tenant must only see their own rows. Of those, a finance or operations team that lives in spreadsheets and needs warehouse-scale data without exporting csvs and an organisation that has consolidated on snowflake or databricks and wants one governed access layer rather than several desktop tools are not what Snowplow is typically brought in for.
What can Sigma Computing do that Snowplow cannot?
Sigma Computing covers Spreadsheet interface over SQL, No extract layer, Input tables and write-back, Workbooks. Snowplow covers Own-cloud deployment, Schema enforcement, Warehouse loading, Enrichment.

Answered from the vendors’ own pages

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.

Snowplow: Is Snowplow still open source?

Not in the permissive sense. On 8 January 2024 the core pipeline moved from Apache 2.0 to the Snowplow Limited Use Licence Agreement, with version 1.1 following in December 2024, alongside a community licence based on the Confluent Community Licence. Trackers and analytics SDKs remain Apache 2.0.

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.

Snowplow: Can we still run it for free in production?

Free use of the relicensed core components is materially constrained and commercial use generally requires an agreement. Read the current licence text against your intended use rather than relying on older documentation.

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.

Snowplow: Is there an Apache 2.0 alternative?

Yes, a fork called OpenSnowcat was created in response to the relicensing and continues under Apache 2.0.

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.

Snowplow: What does Snowplow BDP cost?

Not published. It is quoted by event volume and deployment, and your own cloud infrastructure costs are separate and additional.

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