Embeddable vs Power BI: A Guide for SaaS Teams

SaaS teams evaluating embedded analytics often compare two fundamentally different approaches.

Power BI is a powerful enterprise BI suite optimized for internal reporting inside Microsoft ecosystems.

Embeddable is a developer first toolkit purpose built for customer facing analytics in SaaS products.

This guide compares both tools across architecture, developer experience, UX customization, performance, security, multi tenancy, pricing and migration complexity, with clear source informed analysis to help engineering and product leaders decide faster.

TLDR

Power BI

• Excels for enterprise internal reporting and Microsoft centric stacks.
  
• Embedding has many BI features but UI is inflexible and it’s iframe based.
  
• Requires Premium licensing or Embedded capacity for production use.
  
  

Embeddable

• Optimized for customer facing SaaS analytics.
  
• Uses native embedding with no iframes.
  
• Offers deep customization and multi tenant RLS models.
  
• Uses scalable caching.
  
• Has fixed pricing for unlimited users.
  
  

Quick Overview

Embeddable vs Power BI at a Glance

Embedding method

Embeddable

• Native DOM rendering via web components, React and Vue.
• No iframes.
• Two way interaction with your app.

Power BI‍

• Iframe based embedding through Power BI Embedded.
• Relies on the Power BI Service user interface.
• Requires workarounds to handle auth
  
  

Customization

• Embeddable - Fully customizable components. Matches your design system & supports custom charts.
  

• Power BI - Limited customization. Always looks like Power BI, even when themed.
  
  

Performance

• Embeddable - Multi level caching including L1 in memory cache and L2 pre aggregations. Optimized for multi tenant SaaS workloads.
  

• Power BI - Performance depends on workspace capacity. Heavy dashboards can load slowly in embedded contexts.
  
  

Multi tenancy

• Embeddable - Server issued security tokens. Row level, column level and tenant level isolation.
  

• Power BI - RLS supported using dataset roles. Often requires separate datasets or multiple roles per tenant.
  
  

Setup time

• Embeddable - Fast setup. No Microsoft ecosystem required.
  

• Power BI
  
  • Requires Power BI Service, workspaces, datasets and dataflows.
  • Requires Azure AD configuration and workspace permissions.
  • Needs capacity planning for Embedded or Premium.
    
    

Integration depth

• Embeddable - Full control over state, variables and events. Embedded components render inside your DOM.
  

• Power BI - Power BI runs inside an iframe. Integration and communication rely on the Power BI JavaScript API.
  
  

Pricing

• Embeddable - Flat, predictable pricing with unlimited users.
  

• Power BI - Uses Power BI Embedded A SKUs or Premium P SKUs. Pricing is based on capacity, usage and concurrency.
  
  

Deployment options

• Embeddable - Cloud or self hosted deployment.
  

• Power BI - Cloud or self hosted deployment.
  
  

End user experience

• Embeddable - Feels fully native to your application.‍

• Power BI - Feels like Power BI has been embedded inside your interface.
  
  

What Is Power BI

Overview and core philosophy

Power BI is Microsoft’s enterprise business intelligence platform.

It focuses on internal reporting, deep Azure integration and strong modeling capabilities for analysts.

It is built for enterprises rather than SaaS products and excels where internal teams need governance heavy analytics.

Strengths of Power BI

• Enterprise grade semantic modeling, including datasets, dataflows and DAX.
• Wide range of traditional BI features
• Strong integration with Microsoft environments such as Azure Synapse, Excel, Fabric and Dynamics.
  
  

Limitations of Power BI for embedded SaaS use cases

• Embedding is iframe based with limited UI control.
• Dashboards still look and behave like Power BI rather than your application.
• Requires Azure AD token generation, authentication pipelines and workspace governance.
• Requires Premium or Embedded capacity for production embedding.
• The enterprise focused UX is not optimized for modern SaaS products.

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What Is Embeddable

Overview and philosophy

Embeddable is a developer-first analytics embedding toolkit for SaaS teams.

It is designed for teams that want native feeling, customizable and high performance analytics inside their product, without iframe limitations or BI tool UX constraints.

Teams model data, define components and embed dashboards directly in their DOM using modern web frameworks.

Key strengths of Embeddable

• Native rendering with no iframes.
• High performance through multi tier caching.
• Powerful self-serve custom dashboard builder for end users.
• Globally scalable RLS designed for multi-tenant SaaS.
• Fully customizable and extensible user interface and styling.
• Developer ownership, with versioning and CI CD compatibility.
• Fast time to value for product, engineering and design teams.
  
  

Ideal use cases for Embeddable

• Customer facing dashboards inside SaaS products.
• Multi tenant environments with large concurrent usage.
• Replacing iframe based BI tools with a modern analytics architecture.
• Replacing expensive custom built analytics with a maintainable toolkit.
  
  

Feature Comparison Deep Dive

1. Developer experience

Power BI

• Requires use of Power BI Desktop, datasets, dataflows and reports.
• Embedding requires Azure AD applications, embedding tokens and workspaces.
• Iframe based embedding restricts deep UX integration.
• Interactivity relies on the Power BI JavaScript API.
• Custom visuals require TypeScript development, packaging and deployment.
  

Embeddable

• Simple setup.
• Native SDKs for JavaScript, React and Vue.
• Full DOM control, event listeners and reactive variables.
• Versioning and staging environments are built in.
• Charts and dashboards can be defined in code or created with the no code builder.
  

What it implies

Power BI demands deep involvement in the Microsoft ecosystem.

Embeddable integrates directly into modern SaaS engineering workflows without infrastructure overhead.

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2. Performance and scalability

Power BI

• Performance is tied to workspace capacity.
• Heavy dashboards often feel slow when rendered inside iframes.
• Cross origin communication increases latency.
• The full report user interface must render before queries can run.
  

Embeddable

• L1 in memory caching for hot queries.
• L2 pre aggregations for large datasets and complex workloads.
• Caching API for orchestrating refresh logic and tenant specific strategies.
• Lightweight DOM native rendering for fast user experience.
  

Performance with complex retail data has been excellent, with millions of records processed without issues. - Alejo B., Chief Data Officer on G2.

What it implies

Power BI can perform well with enough capacity, but embedding overhead introduces latency.

Embeddable delivers consistently fast loading times for customer facing, data heavy environments.

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3. UI customization and design fidelity

Power BI

• Limited theming and styling.
• Cannot fully adopt your spacing, layout, typography or interaction design.
• The Power BI toolbar and container are always present.
• It always looks like Power BI, regardless of branding.
• Iframe boundaries restrict interaction patterns with the rest of your app.
  

Embeddable

• Native rendering inside your DOM.
• Full control over CSS, JavaScript and component structure.
• You can bring your own charting libraries or custom visuals.
• End users can build dashboards that still feel like your product.
• There is no BI tool look or behavior imposed by the platform.
• Embeddable adapts to our brand and styling requirements seamlessly.

What it implies

Power BI is suitable if you accept Power BI’s user interface.

Embeddable is ideal if you need dashboards that look and behave like your product.

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4. Security and multi tenancy

Power BI

• RLS is supported via roles on datasets.
• Each tenant often requires separate datasets or carefully managed RLS roles.
• Embedding relies on Azure AD and token exchange.
• Governance features expand only with Premium capacity.
  

Embeddable

• Tenant aware security tokens define access at row, column and object level.
• Per tenant access policies scale without dataset duplication.
• SOC2 Type 2, GDPR compliance, encryption and enterprise grade security are supported.
• The intuitive RLS system makes it easy to manage who sees what.

What it implies

Both platforms support RLS, but Embeddable’s model is designed specifically for SaaS multi-tenancy.

Power BI is primarily designed for internal enterprise analytics.

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5. Pricing and ROI

Power BI

• Embedding requires Power BI Embedded A SKUs or Premium P SKUs.
• Pricing is tied to capacity, virtual cores and refresh workload.
• Costs grow with tenants, usage and concurrency.
• It can become expensive as your customer base scales.
  

Embeddable

• Flat, predictable pricing.
• Unlimited users, viewers and dashboards.
• No capacity planning is required.
• Lower long term engineering overhead due to simpler architecture.

What it implies

Power BI works well for internal analytics.

For customer facing SaaS use cases, cost grows quickly as you scale, while Embeddable remains predictable.

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When to Choose Power BI

Best for

• Enterprise internal reporting.
• Organizations deeply committed to the Microsoft ecosystem.
• Teams that are comfortable with Power BI Desktop and DAX modeling.
  
  

Where it falls short

• Dashboards do not feel native in a SaaS application.
• Iframe based user experience.
• Limited customization and control over UX.
• Becomes expensive at scale.
• Multi tenancy becomes complex for large customer bases.
  
  

When to Choose Embeddable

Best for

• SaaS products with customer facing dashboards.
• Teams that want full control over UX.
• Multi tenant environments requiring scalable RLS.
• Developer driven organizations with CI CD needs.
  
  

Added value

• No iframe overhead.
• Native rendering that feels built into your product.
• Predictable pricing as you scale.
• Better performance for data heavy and interactive dashboards.
• Reduced engineering effort compared to custom builds and traditional BI tools.
• Powerful end-user self-serve features
  
  

Case Studies and Proof Points

• Pledge, for supply chain sustainability analytics.
  
• Fashion Cloud, with new revenue opportunities driven by embedded analytics.
  
• Resident Advisor, with large scale live event data analytics.
  
• HONK, with improved product management experimentation and reduced engineering load.
  
• mpathic AI, with seamless branding and user experience integration.
  
  

FAQ

Is Power BI good for embedded analytics

It is suitable for simple embedding and internal use. Iframe user experience and enterprise heavy UI make it less ideal for SaaS applications.

Does Power BI support multi tenancy

Yes, through datasets and RLS roles. Setup requires careful management of roles, datasets and Azure AD. It is not designed primarily for SaaS scale multi tenancy.

Does Embeddable support multi tenant RLS

Yes, through per tenant security tokens and flexible access policies.

How customizable is Power BI

Customization is limited. Pages, containers and toolbars remain recognisably Power BI.

How customizable is Embeddable

Very customizable. You have full DOM control and can integrate your design system completely. In addtion your end-users can build their own views of dashbaords.