Sigma
Spreadsheet-style analytics on your cloud data warehouse — no SQL required, no data copies, full governance.
Overview
Sigma is a cloud-native analytics and business intelligence platform that lets business users explore live data directly in their cloud data warehouse — Snowflake, Databricks, BigQuery, Redshift, and more — through a familiar spreadsheet interface. All computation runs inside the warehouse itself, so there are no data extracts, no stale caches, and no loss of existing security controls. Finance, operations, and product teams can build pivot tables, write formulas, run SQL or Python, and collaborate in real time on the same workbook without waiting for an engineer.
In 2026, Sigma expanded into agentic analytics with Sigma Agents — no-code AI agents that execute autonomous or user-approved workflows entirely inside the warehouse's governance boundary — and launched its APJ headquarters in Sydney to serve Asia Pacific customers. The company surpassed $200 million ARR in April 2026 and raised an $80 million Series E at a $3 billion valuation, backed by Databricks Ventures, ServiceNow Ventures, and Workday Ventures alongside its existing investors.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 16 Jun 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
Use cases
What you can produce with Sigma
- Live, governed BI dashboards connected directly to your cloud data warehouse with no data extracts
- Collaborative spreadsheet workbooks with real-time co-authoring, version history, and rollback
- No-code AI agents (Sigma Agents) that run autonomous or user-approved data workflows inside warehouse governance
- Embedded analytics portals integrated into third-party applications via JWT-secured iframes and React SDK
- Write-back Input Tables enabling FP&A and data entry use cases directly into warehouse tables
- AI-assisted data exploration via Sigma Assistant natural-language query copilot
- MCP Server integration enabling governed AI chat tools to query warehouse data under existing access controls
ASEAN Perspective
Sigma in Southeast Asia
Sigma opened its Asia Pacific and Japan headquarters in Sydney, Australia in February 2026, appointing Bede Hackney as VP APJ and launching AWS ap-southeast-2 region support — a meaningful step toward local data residency for Australian and, by extension, Southeast Asian customers. However, Sigma has no reported office presence in Singapore, Malaysia, or other ASEAN markets, and its partner ecosystem lists no ASEAN-specific system integrators. Enterprises in the region must route through the Sydney team, and data sovereignty requirements outside Australia may still require bespoke arrangements with Sigma's sales team.
Sigma earns high marks for capability and usability among teams already operating on Snowflake or Databricks. Its zero-copy, live-warehouse architecture and real-time co-authoring genuinely differentiate it from extract-based BI tools, and the 2026 pivot to Sigma Agents signals a credible path toward AI-driven, governed analytics workflows. Enterprise customers like JPMorgan Chase and AMD demonstrate that it can handle serious production workloads.
That said, Sigma is not a one-size-fits-all solution. The platform requires an existing cloud data warehouse — organisations without one face significant setup costs before they can evaluate Sigma's value. Pricing is entirely custom and opaque, with median annual contracts around $60K and substantial add-on costs for embedded analytics and additional warehouse compute. APAC presence is still nascent; the Sydney APJ office only opened in February 2026, and Southeast Asian coverage remains thin. Teams evaluating against Looker or ThoughtSpot should weigh vendor lock-in risk carefully.
What people say
Sigma earns strong marks on G2 and Gartner Peer Insights, with reviewers praising its spreadsheet-familiar interface, real-time collaboration, and zero-copy warehouse architecture that queries cloud data without extracts. Critics flag opaque, custom-only enterprise pricing, limited support for non-warehouse and NoSQL sources, and iframe-centric embedding as recurring pain points. Gartner has recognised Sigma in its Analytics and BI Platforms Magic Quadrant. For Snowflake- and Databricks-centric organisations, Sigma is a top-tier self-service BI choice; teams needing broad multi-source connectivity or deeply customised customer-facing embedded analytics should evaluate alternatives alongside it.
Summary of public user & expert reviews, compiled by RECATOOLS.
Notable facts
- Sigma was originally incorporated as 'Bitmoon Computing' in 2014 before rebranding; it shortened its name again from 'Sigma Computing' to simply 'Sigma' in 2024.
- Sigma Agents — its no-code AI agents for warehouse-native automation — became the fastest-adopted product in the company's history within the first quarter of launch in 2026.
- Sigma's Series E strategic investors read like a who's who of the modern data stack: Databricks Ventures, ServiceNow Ventures, and Workday Ventures all bet on the same platform in a single round.
- All Sigma computation runs inside your existing warehouse — no data is ever extracted or copied to Sigma's servers, meaning your Snowflake or Databricks access controls automatically govern every query.
Frequently asked questions
About this listing
This entry was compiled from publicly available data including Sigma's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Sigma unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
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