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Competitor comparison

Sigma vs Snowflake CoWork

Sigma puts a spreadsheet-style workbook on live warehouse tables for finance and ops power users, while Snowflake CoWork lets people ask those same tables questions in plain English.

Quick decision snapshot

Pick Sigma if your users think in grids and formulas and want to build workbooks, input tables, and dashboards directly on Snowflake without writing SQL. Pick Snowflake CoWork if most users just want to ask a question and get a number, and your data team will define the business logic in semantic views. On BI Bench, Snowflake CoWork scored higher than Sigma; Sigma was faster.

Two interfaces for the same Snowflake tables

Sigma and CoWork are a natural pairing for Snowflake customers. Sigma has deep Snowflake roots and queries live warehouse tables rather than extracts, and CoWork works on governed data inside Snowflake by definition. Neither moves data elsewhere. The real question is which interaction model suits your users: building in a spreadsheet, or asking in a sentence.

Sigma's answer is the spreadsheet. Finance and operations analysts already know formulas, pivots, and grids, and Sigma gives them that experience on warehouse-scale data, plus input tables and dashboards for sharing. Adoption can be quick among spreadsheet-comfortable users. As usage spreads, workbook sprawl and inconsistent formulas need standards from the data team to keep under control. On BI Bench, Sigma placed ninth with 35.2% accuracy and a 42.6-second average.

CoWork for the manager who just wants a number

CoWork aims at the users Sigma does not reach: the manager who wants one number and will not build a pivot. Its agents use Cortex Analyst to turn the question into SQL over a semantic view, which defines metrics, entities, and relationships, and run it within the role and row-policy rules Snowflake already applies. Users ask on the web or in the iOS app and get answers with charts or tables.

That convenience depends on the semantic views, and answer quality follows how carefully the data team curates them. Follow-up questions keep context, but the hands-on slicing Sigma users do in a grid is a different way of working than asking in chat.

Grid versus question on Snowflake

CriterionSigmaSnowflake CoWork
How users workBuild workbooks with formulas, pivots, and input tablesType a question and read the answer
Ideal userFinance and ops power users fluent in spreadsheetsOccasional askers who want a number quickly
Iterating on a resultNatural; adjust the workbook and recalculateAsk a follow-up; the conversation keeps context
Where logic livesWorkbook formulas, governed by data-team standardsSemantic views set up by the data team
BI Bench on defaults9th: 35.2%, 42.6s3rd: 81.1%, 55.5s
WarehousesCloud warehouses, with deep Snowflake heritageSnowflake only
Governance riskWorkbook sprawl if standards are looseWrong answers if semantic views are thin

Sigma is the better fit for

FP&A and operations teams who model in spreadsheets today.

Workflows built on input tables and formulas over live data.

Analysts who want to iterate on a result rather than re-ask it.

CoWork is the better fit for

Executives and managers who want answers without learning a tool.

Stakeholders who want a recurring report emailed from a question.

Domains where a few well-defined metrics cover most questions.

Questions that turn into dashboards

Sigma asks users to build, and Snowflake CoWork gives them answers in chat. Basedash sits between the two: someone asks in plain English, gets a chart backed by SQL they can inspect, and can save it to a dashboard, schedule it, or send it to Slack. Its BI Bench accuracy, 95.8%, was ahead of Snowflake CoWork's 81.1% and well ahead of Sigma's 35.2%, and it connects to Snowflake, other warehouses, and SaaS tools through built-in Fivetran.

Finance teams that need spreadsheet formulas and input tables on warehouse data will still be happier in Sigma.

Also compare each against Basedash

FAQ

Can Sigma and Snowflake CoWork be used together?

Yes, and the roles split cleanly. Power users build and maintain workbooks and dashboards in Sigma on live Snowflake tables, while occasional users ask quick questions in CoWork on the web or in its iOS app. Both query Snowflake directly, so data does not move. The thing to manage is definitions: Sigma's logic sits in workbook formulas and CoWork's in semantic views, so a key metric can end up defined twice.

Is Sigma or Snowflake CoWork better for finance teams on Snowflake?

Sigma, for most finance work. FP&A analysts tend to iterate: they slice a number, adjust an assumption, and compare scenarios, which suits Sigma's formulas, pivots, and input tables on live data. CoWork handles questions and follow-ups in chat, but scenario work in formulas and input tables is not how it operates. CoWork is useful for finance stakeholders who want a quick figure, such as last month's revenue, or a recurring emailed summary, once a semantic view covers it.

How did Sigma and Snowflake CoWork compare on BI Bench?

Sigma landed in ninth place, meeting 35.2% of the grading criteria in 42.6 seconds on average. Snowflake CoWork placed third at 81.1%, averaging 55.5 seconds. The benchmark tested out-of-the-box behavior on one shared, complex schema, so a tuned semantic setup could change either number. Basedash, the leader, scored 95.8% at 20.9 seconds.

When does Basedash make more sense than Sigma or Snowflake CoWork?

When most of your users are neither spreadsheet power users nor content with answers in chat, and they need dashboards they can build by describing them. Basedash writes reviewable SQL from plain-English requests, publishes to dashboards, scheduled reports, and Slack, and connects to Snowflake plus SaaS tools through Fivetran. BI Bench ranked it first. Spreadsheet-heavy finance teams may still prefer Sigma.

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