Why teams choose Sigma vs Omni
Semantic Portability
Protect existing investments. Sigma natively integrates with dbt and Snowflake Semantic Views, allowing externally built metrics to flow directly into Sigma without re-definition.
Sigma Agents
Turn insights into automated work. Sigma Agents read, write, and trigger external workflows while inheriting warehouse security, ensuring every action is fully auditable.
AI Applications
Move beyond read-only dashboards. Empower all users to build interactive AI Apps so that they can take action and safely write decisions directly back to your cloud data warehouse.
Secure Governance
AI security must be architectural. Sigma Agents and AI Apps automatically inherit your cloud data warehouse Row-Level Security (RLS) and Column-Level Security (CLS).
Enterprise SDLC
Get production-grade controls without the engineering overhead. Sigma isolates draft and live states using connection-aware deployment and version tagging.
AI Ecosystem
Sigma is your OS for live data and AI. Securely unify external agents via MCP with warehouse LLMs and Sigma Agents for natural language discovery and action without vendor lock-in.
AI, Apps, and Agents with all the BI that you expect.
We excel in the cloud
Analyze billions of rows of live warehouse data using spreadsheet formulas you already know. No stale extracts, row limits, or proprietary coding languages. Ask Sigma Assistant if you have a question.
Dashboards built the way you’ve always wanted
Use Sigma Assistant to help you build dynamic, interactive dashboards without writing SQL or waiting on data engineering. Drill down to the underlying row level instantly on live, governed data.
Write directly back to your warehouse
If you know how to use a spreadsheet, you can safely capture data, run live scenarios, and trigger downstream workflows. Deploy Sigma Agents to fully automate those actions with a complete audit trail.
Scale with unmatched performance
Securely embed live analytics and writeback capabilities into your customer portals. Automatically inherit warehouse security for strict multi-tenant data isolation without duplicate permission models.
Sigma is the enterprise leader in self-service analytics and operational workflows.
FEATURE COMPARISON
As of March 29, 2026
Sigma
Omni
AI Applications
Move beyond read-only dashboards with AI Apps and Sigma Agents. All users can build and deploy no-code interactive applications with embedded autonomous agents that answer questions, securely trigger external workflows, and natively write governed decisions back to your cloud data warehouse.
Constrained by a proprietary semantic layer, Omni operates strictly as an antiquated answer or read-only tool. It is structurally incapable of agentic action. Building interactive applications or automated workflows requires exporting sensitive data to external tools, instantly creating shadow AI infrastructure.
Governed Writeback
Capture inputs and trigger workflows safely via Input Tables. Every user writeback and Sigma Agent action automatically inherits your cloud data warehouse’s native permissions and security policies, ensuring absolute enterprise governance.
Fundamentally a read-only reporting tool. Capturing user inputs, planning scenarios, or triggering actions requires exporting data or buying disconnected third-party workflow platforms.
Warehouse-Native Functions
Sigma compiles compute pushdown directly, ensuring teams can invoke warehouse-native AI functions, custom UDFs, and ML models in Snowflake and Databricks without ever extracting the underlying data.
External caching architecture separates data from your native compute layer. To leverage warehouse-native AI functions or UDFs, users are forced to write complex custom SQL, severely limiting adoption.
Data Modeling
Natively integrate with dbt and Snowflake Semantic Views so centrally defined metrics flow directly into AI Apps and Sigma Agents without re-definition. This shared semantic foundation ensures automated actions execute with governed precision and complete auditability.
Requires OmniML for dashboards and exploration, creating a hard data team dependency for joins and metrics. Users are locked into a predefined semantic layer, reintroducing the legacy LookML bottleneck. This traps teams in a ticketing and context-switching cycle incompatible with the pace of modern agentic workflows.
Data Exploration
Explore data freely using familiar spreadsheet syntax and a no-code GUI, without relying on data teams or predefined questions.
Accurate answers require OmniML, creating a predefined semantic dead-end. Iterative exploration is paralyzed by forcing business users to rely on the data team for new questions.
Drill Down
Flexible paths allow users to drill infinitely into any data point at billion-row scale using any field, securely querying the live warehouse without pre-aggregation.
Drill paths in OmniML are rigid and predefined, limiting users’ ability to explore metrics on their own.
True Self-Service
Enable all users to build AI Apps and Sigma Agents to drive closed-loop workflows using a familiar spreadsheet UI and formulas combined with native writeback. Zero proprietary code and no row limits mean zero barriers between discovering insights at billion-row scale and building the applications to act on them.
Ad-hoc calculations face arbitrary row limits, forcing self-service on sampled, potentially inaccurate data. A lack of governed, native writeback drives teams to abandon the platform entirely just to execute a complete operational workflow. Omni's read-only architecture makes building and deploying agentic workflows structurally impossible for business teams.
Collaborative Workflows
Sigma's architecture enables real-time, synchronous, agentic collaboration. Multiple users can build, edit, and explore the same live workbook simultaneously without locking files or overwriting work. This shared environment natively supports human-in-the-loop approval chains, allowing teams to securely review and approve Sigma Agent actions before execution.
Omni users are restricted to a legacy, single-player architecture. Attempting to co-edit causes file locks and overwritten work, stalling momentum. This lack of a synchronous workspace means Omni cannot support collaborative AI development or human-in-the-loop workflows, forcing teams to rely on disconnected communication tools for governance.
Security
Sigma's zero-copy architecture natively inherits warehouse Row-Level Security (RLS) and Column-Level Security (CLS) via OAuth passthrough. No data extraction, and zero duplicate permission models to manage.
Utilizes external caching to store data outside the warehouse, introducing data movement, governance challenges, and potential accuracy issues when users unknowingly query cached subsets instead of live warehouse data.
Version Control
Sigma isolates draft and live states using connection-aware deployment and version tagging. Track changes to everything and allow granular reversion to facilitate enterprise application lifecycle management (ALM).
Lacks native application lifecycle management (ALM) features, forcing data teams to rely on external tools. This severely complicates iterative, collaborative development, increasing the risk of breaking live business workflows.
SQL Editing
Sigma provides a robust SQL editor that can effectively handle mixed querying, allowing for analysts to do ad-hoc analysis and share results.
Omni supports custom SQL queries, but does not allow mixed querying, limiting analysis.
In-Product Customer Support
All Sigma users have access to live, in-product chat support averaging a 23-second initial response time from a real human, ensuring zero lost app and agent building momentum.
Omni provides documentation and a chat mechanism to inform troubleshooting around its inherent architectural flaws and read-only constraints.
Sigma
Omni
AI Applications
Move beyond read-only dashboards with AI Apps and Sigma Agents. All users can build and deploy no-code interactive applications with embedded autonomous agents that answer questions, securely trigger external workflows, and natively write governed decisions back to your cloud data warehouse.
Constrained by a proprietary semantic layer, Omni operates strictly as an antiquated answer or read-only tool. It is structurally incapable of agentic action. Building interactive applications or automated workflows requires exporting sensitive data to external tools, instantly creating shadow AI infrastructure.
Governed Writeback
Capture inputs and trigger workflows safely via Input Tables. Every user writeback and Sigma Agent action automatically inherits your cloud data warehouse’s native permissions and security policies, ensuring absolute enterprise governance.
Fundamentally a read-only reporting tool. Capturing user inputs, planning scenarios, or triggering actions requires exporting data or buying disconnected third-party workflow platforms.
Warehouse-Native Functions
Sigma compiles compute pushdown directly, ensuring teams can invoke warehouse-native AI functions, custom UDFs, and ML models in Snowflake and Databricks without ever extracting the underlying data.
External caching architecture separates data from your native compute layer. To leverage warehouse-native AI functions or UDFs, users are forced to write complex custom SQL, severely limiting adoption.
Data Modeling
Natively integrate with dbt and Snowflake Semantic Views so centrally defined metrics flow directly into AI Apps and Sigma Agents without re-definition. This shared semantic foundation ensures automated actions execute with governed precision and complete auditability.
Requires OmniML for dashboards and exploration, creating a hard data team dependency for joins and metrics. Users are locked into a predefined semantic layer, reintroducing the legacy LookML bottleneck. This traps teams in a ticketing and context-switching cycle incompatible with the pace of modern agentic workflows.
Data Exploration
Explore data freely using familiar spreadsheet syntax and a no-code GUI, without relying on data teams or predefined questions.
Accurate answers require OmniML, creating a predefined semantic dead-end. Iterative exploration is paralyzed by forcing business users to rely on the data team for new questions.
Drill Down
Flexible paths allow users to drill infinitely into any data point at billion-row scale using any field, securely querying the live warehouse without pre-aggregation.
Drill paths in OmniML are rigid and predefined, limiting users’ ability to explore metrics on their own.
True Self-Service
Enable all users to build AI Apps and Sigma Agents to drive closed-loop workflows using a familiar spreadsheet UI and formulas combined with native writeback. Zero proprietary code and no row limits mean zero barriers between discovering insights at billion-row scale and building the applications to act on them.
Ad-hoc calculations face arbitrary row limits, forcing self-service on sampled, potentially inaccurate data. A lack of governed, native writeback drives teams to abandon the platform entirely just to execute a complete operational workflow. Omni's read-only architecture makes building and deploying agentic workflows structurally impossible for business teams.
Collaborative Workflows
Sigma's architecture enables real-time, synchronous, agentic collaboration. Multiple users can build, edit, and explore the same live workbook simultaneously without locking files or overwriting work. This shared environment natively supports human-in-the-loop approval chains, allowing teams to securely review and approve Sigma Agent actions before execution.
Omni users are restricted to a legacy, single-player architecture. Attempting to co-edit causes file locks and overwritten work, stalling momentum. This lack of a synchronous workspace means Omni cannot support collaborative AI development or human-in-the-loop workflows, forcing teams to rely on disconnected communication tools for governance.
Security
Sigma's zero-copy architecture natively inherits warehouse Row-Level Security (RLS) and Column-Level Security (CLS) via OAuth passthrough. No data extraction, and zero duplicate permission models to manage.
Utilizes external caching to store data outside the warehouse, introducing data movement, governance challenges, and potential accuracy issues when users unknowingly query cached subsets instead of live warehouse data.
Version Control
Sigma isolates draft and live states using connection-aware deployment and version tagging. Track changes to everything and allow granular reversion to facilitate enterprise application lifecycle management (ALM).
Lacks native application lifecycle management (ALM) features, forcing data teams to rely on external tools. This severely complicates iterative, collaborative development, increasing the risk of breaking live business workflows.
SQL Editing
Sigma provides a robust SQL editor that can effectively handle mixed querying, allowing for analysts to do ad-hoc analysis and share results.
Omni supports custom SQL queries, but does not allow mixed querying, limiting analysis.
In-Product Customer Support
All Sigma users have access to live, in-product chat support averaging a 23-second initial response time from a real human, ensuring zero lost app and agent building momentum.
Omni provides documentation and a chat mechanism to inform troubleshooting around its inherent architectural flaws and read-only constraints.
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