Looker has a clear lead for embedded analytics with tenant-specific access controls and theming without duplicated dashboards. For SaaS teams building analytics components into their front end, Embeddable emphasizes a single dashboard definition with security at the data-modeling layer.
LookerChatGPT Search92%Google AI Mode51%ChatGPT SearchGoogle AI Mode
QrveyChatGPT Search42%Google AI Mode62%ChatGPT SearchGoogle AI Mode
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Questions and answers
I'm looking for a way to embed dashboards directly into our SaaS application. What's the best embedded analytics platform for a multi-tenant environment?
I need an embedded analytics tool that handles row-level security and custom themes per tenant, but I don't want to create separate dashboard versions for each one. What are my options?
What are the best embedded BI platforms that allow for tenant-specific branding and row-level security while maintaining a single dashboard definition?
Which embedded analytics platforms support row-level security and tenant-specific theming without duplicating dashboard definitions?
White-Labeling: The analytics interface should seamlessly match your application's design system, typography, and dark/light modes without showing third-party branding.
Authentication & Tokenization: Look for secure JWT (JSON Web Token) or SSO handshakes to pass user identity, roles, and tenant context from your SaaS backend to the analytics layer seamlessly.
Best embedded analytics platforms for multi-tenant SaaS
My recommendation: shortlist Omni, Embeddable, and Qrvey first if you're building customer-facing analytics into a multi-tenant SaaS product. I'd also evaluate Metabase if cost and implementation simplicity matter, and Sigma if customers need to do more than view dashboards.
The key is to choose a platform designed for customer-facing embedded analytics, not just a traditional BI tool that happens to support iframes. In a multi-tenant environment, every customer must see only the data they're authorized to access, while your team maintains consistent metrics, branding, and performance as the customer base grows.
My top 5 options
1. Omni
(Best for governed analytics)
A strong choice if you need customer-facing dashboards, a shared semantic layer for consistent metrics, and secure embedding with user-specific access controls. Especially worth evaluating if you want to add AI-driven analytics later.
Trade-off: You'll need a well-modeled data warehouse and should validate the tenant model against your architecture.
A great candidate if dashboards should look and behave like a natural part of your app. Its component-oriented approach offers more front-end control than a conventional iframe.
Trade-off: More integration work falls on your engineering team, including the design and testing of secure tenant-specific access.
Designed specifically around embedding analytics in SaaS applications, with multi-tenant data handling, white-labeling, and row-, column-, and schema-level security options.
Trade-off: Assess its broader platform footprint, integration requirements, and commercial terms before committing.
Worth a serious look if you want a familiar BI experience, an open-source starting point, and a relatively straightforward route to embedded dashboards. Its paid Pro and Enterprise tiers offer dedicated tenant-management features for SaaS use cases.
Trade-off: Advanced permissions, full-app embedding, and white-labeling may require paid plans.
A strong option if your customers need spreadsheet-like exploration, interactive reporting, and potentially data-editing workflows in addition to dashboards. Secure embedding uses signed URLs and supports tenant-aware security controls.
Trade-off: Evaluate the cost and complexity of the broader analytics experience if you only need a few simple charts.
I would evaluate these capabilities in roughly this order.
Requirement
What to verify
Tenant isolation
Each request is scoped to the authenticated tenant on the server, not just filtered in the browser.
Row-level security (RLS)
Users can query only the rows permitted by their identity and tenant membership.
White-labeling
Your logo, colors, fonts, domain, and navigation can match your application.
Embedding SDK
React components or web components if you want a native feel; an iframe if speed is the priority.
Pricing at scale
Cost for customer accounts, monthly active viewers, usage, and production environments—not just developer seats.
These are important distinctions because secure embedding and actual data authorization are different things. For example, Metabase documents specific tenant controls on paid tiers, while Sigma documents secure embedding through signed URLs and runtime security settings.
One non-negotiable: Never trust a tenant ID supplied by the browser as the sole security boundary. Derive or validate tenant identity on your server, sign embed credentials there, and test that users cannot access another tenant's data through altered filters, exports, saved reports, or API calls.
Which would I choose?
Omni if governed metrics and analytics that can expand into AI are central to your product.
Embeddable if your product team prioritizes a seamless UI and deep front-end customization.
Qrvey if you want a platform explicitly oriented toward multi-tenant SaaS analytics.
Metabase if you want a practical, potentially lower-cost starting point.
Sigma if customers need powerful, interactive data exploration.
These are starting recommendations, not a universal ranking. Pricing, licensing, security configuration, and feature availability should be confirmed directly with each vendor.
Let's narrow it down to your use case
I can give you a much more specific recommendation if I know one thing: what kind of embedded analytics experience are you building?
1. What will your customers do?
View predefined dashboards and reports
Create their own reports and explore data
Use analytics that feel like native app components
Omni — shared semantic model with tenant-specific access filters and white-label/CSS theming; particularly designed around embedded SaaS.
Power BI Embedded — dynamic RLS can let multiple customers use one report/semantic model, but Microsoft also recommends workspace isolation for some large-scale scenarios.
If “define once, vary security + branding per tenant” is the core requirement, I’d shortlist Sigma, Looker, and Omni for a proof-of-concept.
Bold BI — Supports a single-site multi-tenancy architecture where data is filtered at query execution using JWT claims for RLS, combined with runtime branding options to alter logos, color palettes, and fonts per tenant context.[](https://www.boldbi.com/multitenancy/)
If you'd like to narrow down which option fits best, let me know:
Are you looking for a headless/code-first developer toolkit (like Cube or Embeddable) or a low-code/drag-and-drop BI tool (like Power BI or Sisense)?
