Sigma

Overview

Sigma's premise is that the spreadsheet already won. Most people who need to work with data are fluent in spreadsheets and not in SQL, so Sigma gives them a spreadsheet interface whose operations compile to queries against the cloud data platform underneath.

The consequence that matters architecturally is that there is no extract. Analysis runs on the warehouse, against live data, at whatever scale the warehouse handles. That removes the row limits and the staleness that come with pulling data into a BI tool's own store, and it puts the cost of a heavy analysis onto the warehouse bill rather than into a separate capacity tier.

It deliberately serves several audiences from one product: ad hoc exploration starting from a table or a chart, dashboards, spreadsheet-driven work, SQL, and code. Sigma's own description names spreadsheets, SQL, dashboards and code as equally valid entry points.

Beyond reporting, it is pitched as a place to build data apps and to embed analytics into another product, which it frames as a runtime layer for analytics, apps and agents on live data rather than a reporting tool. The argument made to buyers is consolidation: build once on governed data rather than buying a separate tool per workflow.

Pricing is not published. The pricing URL redirects to a contact form, so tiers, seat model and any consumption element are all unknown from public sources — a real gap when comparing it against Lightdash, which publishes a headline number, or Domo, which at least publishes its model.

Key features and capabilities

The same headings are used for every bi & dashboards entry, so two tools can be read side by side.

Data modelling and semantic layer

• Analysis runs against the connected cloud data platform, with no extract into a separate store
• Governed data models underpin the spreadsheet surface, so consolidation does not mean ungoverned copies

Charts, dashboards and interactivity

• Dashboards, charts and tables
• A spreadsheet surface as a first-class way to build, not only a way to export

Calculations, AI and natural language

• Ad hoc analysis starting from a table or a chart, saved only if it turns out to be worth keeping
• Four entry points treated as equal: spreadsheets, SQL, dashboards and code
• Positioned as a runtime for agents working on live data, not only for people

Publishing, embedding and collaboration

• Enterprise-grade analytics built for distribution across a business
• Embedding analytics into a customer-facing product is a first-class use case

Security, lineage and certification

• Governed data is the stated basis for building workflows once and reusing them
• Detailed public documentation, so behaviour can be checked before buying

Integrations

• Connects to the cloud data platform as the source of truth rather than replacing it
• Data apps and embedding for putting analytics inside other products

Where it runs and what it costs

• Cloud service, cloud-native, querying the warehouse in place
• Free trial available without a sales conversation
• No published pricing; the pricing page redirects to contact

Pricing

Price on request

Nothing is published. The pricing path on Sigma's own site redirects to a contact form, so tiers, the seat or consumption model and list prices are all unavailable publicly. A free trial exists, so the product can be evaluated before the cost is known.

Vendor pricing page →

Demos and videos

• Sigma documentation Tutorial · help.sigmacomputing.com (the vendor)

About Sigma Computing

Sigma Computing sells cloud-native analytics that queries the customer's data platform directly. It publishes offices in San Francisco, New York and London. It publishes no pricing at all: the pricing path on its own site redirects to a contact form, so plan structure and licensing model cannot be established from public information. Its documentation is open and detailed, and offers a free trial, so the product itself can be evaluated without a sales conversation even though its cost cannot.

sigmacomputing.com