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Mode vs. Omni Analytics

Built from each tool’s researched, reviewed record. Figures are checked against public pricing pages at research time — always confirm current pricing with the vendor before buying.

The short version

Mode starts at Free per seat, versus Omni Analytics at Custom pricing. Omni Analytics carries the higher aggregate rating (4.8/5 vs 4.5/5).

Full comparison

Modefrom Free
Omni Analyticsfrom Custom pricing
Audyense Score56AS*Fair59ASFair
PositioningAnalyst-first BI combining SQL, Python, R, dashboards, and advanced analytics.Governed BI and embedded analytics built around a shared semantic layer.
Free tierYesNo
DeploymentCloud / SaaSCloud / SaaS
Best fitSMB, Mid-market, EnterpriseSMB, Mid-market, Enterprise
Pricing plans
  • StudioFree
  • BusinessCustom pricing
  • EnterpriseCustom pricing
  • Free trialCustom pricing
  • BusinessCustom pricing
  • EmbeddedCustom pricing
  • EnterpriseCustom pricing
Python and R notebooksYes—
Interactive dashboardsYes—
Reusable datasetsYes—
Governed metricsYesSupports dbt Semantic Layer integration.—
Custom data appsYes—
Advanced analyticsYes—
Role-based access controlYesEnterprise feature.—
SQL editorYesYes
Embedded analytics—Yes
Semantic layer / data modeling—Yes
SAML SSO—Yes
Spreadsheet formulas—Yes
AI analytics—Yes
Row and column permissions—Yes
No-code exploration—Yes
Integrations verified—24+
Aggregate rating4.5 · 330 reviews4.8 · 64 reviews
Integrations
SnowflakeAmazon RedshiftGoogle BigQueryPostgreSQLMySQLMicrosoft SQL Server+6 more
SnowflakeDatabricksAmazon RedshiftGoogle BigQueryPostgreSQLMySQL+9 more
Security & compliance—
SOC 2 Type IIHIPAAGDPRCCPA
Pros
  • Native SQL, Python, and R workflow with results flowing into dashboards and reports.
  • Strong bridge between ad hoc analysis, advanced analytics, and self-serve reporting.
  • Reusable datasets and governed metrics reduce repeated analyst work.
  • Custom data apps and embedded analytics expand the use case beyond static dashboards.
  • Shared semantic model keeps business metrics consistent across workbooks and embeds.
  • Supports SQL, spreadsheet formulas, point-and-click exploration, and AI workflows.
  • Strong embedded analytics story with white-labeling and customizable experiences.
  • Detailed security controls including SAML, row/column permissions, and encrypted connections.
Cons
  • The platform is optimized for analyst-led teams rather than pure business-user self-service.
  • Enterprise identity, access, and support capabilities are not part of the free Studio tier.
  • Pricing and packaging are less transparent for Business and Enterprise.
  • Python/R environments and warehouse performance still require data-team administration.
  • Pricing is quote-led and can be challenging to model for large embedded audiences.
  • Advanced modeling and workbook organization take more time to learn.
  • Fast product iteration can mean documentation and UI rough edges for new capabilities.
  • Cloud-only delivery may not suit buyers requiring self-hosted analytics.
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