SaaS teams looking at embedded analytics often end up comparing tools that were built for very different jobs.

Qrvey is a low code analytics and automation platform designed primarily for internal operations and workflow driven analytics, with a strong focus on AWS native deployments and data orchestration.

Embeddable, on the other hand, is a developer-first analytics toolkit built specifically for customer-facing dashboards in SaaS products. It focuses on native embedding, full UI control and performance patterns that hold up in large multi tenant environments.

This guide breaks down how the two approaches differ across architecture, developer experience, customization, performance, security, multi tenancy, pricing and long term maintainability, so product and engineering teams can make a well informed choice.

If you’re building customer-facing analytics inside a SaaS product, Embeddable is usually a better fit than Qrvey because it’s designed for native embedding, scalable multi-tenancy, and product-level UX control. Qrvey is better suited to internal analytics and workflow-driven reporting, particularly in AWS-centric environments.

TLDR;

Qrvey

• Low code BI and automation layer built on AWS.
  
• Embedding relies on iframe based dashboards.
  
• Flexible data ingestion and workflow automation.
  
• UI looks like Qrvey and cannot match your app’s design system.
  
• Multi tenancy requires additional orchestration and AWS level configuration.
  
• Pricing and deployment complexity grow with AWS resources.
  
  

Embeddable

• Designed for customer facing SaaS analytics.
  
• Native DOM embedding with no iframes.
  
• Fully customizable UI and interactions.
  
• Multi layer caching for real time performance.
  
• Tenant aware RLS designed for SaaS scale.
  
• Flat pricing with unlimited users.
  
  

Quick Overview: Embeddable vs Qrvey at a Glance

Embedding method

Embeddable:

• Native DOM rendering via web components, React and Vue.
  
• No iframes.
  
• Two way interaction with your application logic and UI state.
  

Qrvey:

• Embedding relies on iframe based dashboards and forms.
  
• Limited control outside the iframe boundary.
  
• Interaction requires messaging APIs.
  

Customization

Embeddable:

• Fully customizable components with your design system.
  
• Support for custom charts, layouts and interactions.
  

Qrvey:

• Theming options available.
  
• Core dashboard and component styles remain Qrvey.
  
• Limited ability to achieve a native look inside your product.
  

Performance

Embeddable:

• Multi layer caching including L1 in memory and L2 pre aggregations.
  
• Fast rendering designed for customer facing dashboards.
  

Qrvey:

• Performance depends on AWS infrastructure and Qrvey’s orchestration layer.
  
• Embedding via iframes adds UI overhead.
  
• Workflow heavy workloads may introduce latency.
  

Multi tenancy

Embeddable:

• Tenant aware access via server issued tokens.
  
• Simple row level and column level isolation.
  
• No duplication of dashboards required.
  

Qrvey:

• Multi tenancy built around AWS architecture.
  
• Tenants often require separate datasets or workflows.
  
• Higher operational complexity for SaaS scale.
  

Setup time

Embeddable:

• Fast lightweight setup.
  
• Minimal infrastructure.
  

Qrvey:

• Requires AWS ecosystem familiarity.
  
• Requires Qrvey’s ingestion pipeline setup.
  
• Additional configuration for workflows, automation and permissions.
  

Integration depth

Embeddable:

• Dashboards embed directly inside your DOM.
  
• Deep interaction with your product via events, variables and state.
  

Qrvey:

• Dashboards run inside an iframe.
  
• Integration depends on Qrvey’s messaging API.
  
• Limited UI fusion with host application.
  

Pricing

Embeddable:

• Flat predictable pricing.
  
• Unlimited users and dashboards.
  

Qrvey:

• Pricing influenced by AWS resources consumed.
  
• Scaling external analytics can significantly increase compute cost.
  
• Additional licensing for automation and workflows.
  

Deployment options

Embeddable:

• Cloud or self hosted.
  

Qrvey:

• AWS only.
  
• Requires customers to use or migrate to AWS infrastructures.
  

End user experience

Embeddable:

• Feels completely native inside your product.
  

Qrvey:

• Dashboards feel like a BI tool embedded within your UI.
  
• Styling and UX remain Qrvey centric.
  

What Is Qrvey

Overview and core philosophy

Qrvey is an all in one analytics and workflow automation platform built for teams operating entirely inside the AWS ecosystem. It combines data ingestion, transformation, visualization and automation in a single low code environment.

Qrvey’s embedding capabilities enable teams to surface dashboards inside other applications, but these experiences remain Qrvey controlled and iframe based.

Strengths of Qrvey

• Low code interface for building analytics and workflows.
  
• Deep AWS integration with Lambda, S3, SNS and other services.
  
• All in one architecture for ingestion, transformation and automation.
  
• Suitable for internal operational analytics.
  

Limitations for embedded SaaS use cases

• Embedding always uses iframes.
  
• Limited UI customization compared to native components.
  
• Multi tenant SaaS setups require architectural overhead in AWS.
  
• Performance depends on AWS compute and orchestration.
  
• Designed more for internal ops automation than external customer analytics.
  
• Licensing and infrastructure cost increase as workflows scale.
  

What Is Embeddable

Overview and philosophy

Embeddable is a developer first embedding toolkit designed specifically for customer facing SaaS analytics. Dashboards render directly inside your DOM with full UI control and performance patterns built for multi tenant scale.

It provides a modern developer workflow, fine grained control and a UX that feels completely native to your product.

Key strengths of Embeddable

• Native embedding with no iframe boundaries.
  
• Full UI customization and styling.
  
• High performance via multi tier caching and optimized queries.
  
• Secure tenant aware RLS patterns.
  
• End user self serve dashboard builder.
  
• Versioning, environments and CI CD compatibility.
  

Ideal use cases

• SaaS products offering analytics to customers.
  
• Multi tenant workloads with large concurrent usage.
  
• Replacing Qrvey dashboards for true native UX integration.
  
• Consolidating BI tool sprawl and reducing engineering maintenance.
  

Feature Comparison Deep Dive

1. Developer experience

Qrvey:

• Low code builder for dashboards and workflows.
  
• Requires AWS knowledge for deeper modeling.
  
• Embedding logic requires messaging APIs.
  
• Developers have less control over rendering and interactions.
  

Embeddable:

• Full control through code driven components.
  
• Native SDKs for JavaScript, React and Vue.
  
• DOM level access for actions, variables and events.
  
• Clear versioned environments for CI CD.
  

What it implies
Qrvey caters to internal operations teams rather than product engineering teams.
Embeddable aligns with how SaaS teams build, ship and maintain production features.

2. Performance and scalability

Qrvey:

• Performance tied to AWS compute resources.
  
• iframe rendering slows down visual load.
  
• Complex automation workflows can introduce latency.
  
• Scaling requires careful AWS provisioning.
  

Embeddable:

• L1 in memory caching.
  
• L2 pre aggregations for scale.
  
• Caching API for multi tenant refresh control.
  
• Lightweight DOM rendering for fast UX.
  

What it implies
Qrvey can scale but with operational overhead.
Embeddable provides fast predictable performance with minimal infrastructure.

3. UI customization and design fidelity

Qrvey:

• Theming available but core UI remains Qrvey.
  
• Limited layout customization.
  
• iframe boundaries prevent a native unified UX.
  

Embeddable:

• Complete control of styling and interaction.
  
• Embeds blend seamlessly with your app.
  
• Supports custom charts and components.
  

What it implies
Qrvey cannot deliver native product experiences.
Embeddable creates analytics that look and behave exactly like your product.

4. Security and multi tenancy

Qrvey:

• Multi tenancy typically implemented at the AWS level.
  
• Requires separate datasets, workflows or environments per tenant.
  
• Operationally heavy for rapidly scaling SaaS.
  

Embeddable:

• Tenant aware tokens govern data access.
  
• Row level, column level and object level policies.
  
• Zero duplication of dashboards.
  
• Enterprise grade security posture.
  

What it implies
Qrvey supports multi tenancy but not SaaS native scale.
Embeddable is designed to handle thousands of tenants cleanly and programmatically.

5. Pricing and ROI

Qrvey:

• Pricing varies with AWS infrastructure consumption.
  
• Workflows, automation and data processing increase compute cost.
  
• Embedding external analytics can become costly at scale.
  

Embeddable:

• Flat predictable pricing.
  
• Unlimited users, tenants and dashboards.
  
• No scale penalty for external customers.
  

What it implies
Qrvey can be expensive for customer facing analytics at scale.
Embeddable provides predictable economics aligned with SaaS products.

When to Choose Qrvey

Best for

• Internal operational analytics and automation.
  
• Organizations fully committed to AWS workflows.
  
• Low code teams building internal dashboards and forms.
  

Where it falls short

• iframe based UX that feels external to your product.
  
• Limited customization for customer facing visuals.
  
• Multi tenancy complexity at SaaS scale.
  
• AWS infrastructure cost increases as tenants grow.
  
• Not optimized for developer centric embedding.
  

When to Choose Embeddable

Best for

• SaaS products offering analytics to customers.
  
• Teams needing full UI control and native UX.
  
• Multi tenant architectures requiring scalable RLS.
  
• Developer driven organizations wanting modern workflows.
  
• Replacing low code BI tools with maintainable long term architecture.
  

Added value

• No iframe overhead.
  
• Native rendering and seamless UX.
  
• Predictable pricing as you scale.
  
• High performance for interactive dashboards.
  
• Lower engineering effort long term.
  
• End user self serve features included.
  

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.

Closing perspective

Qrvey makes sense when analytics are primarily an internal concern or part of a broader automation and operations workflow, especially for teams already committed to AWS and comfortable trading UI control for low code convenience. It can be effective for internal dashboards, operational reporting and process driven analytics.

Embeddable is a better fit when analytics are part of the product itself. For SaaS teams exposing insights directly to customers, the ability to control UX, performance and multi tenant behavior becomes critical. By removing iframe constraints and treating analytics as a native product feature rather than a bolted on tool, Embeddable allows teams to scale customer facing analytics without sacrificing design consistency, performance or developer ownership.

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FAQs

Is Embeddable better suited for SaaS products than Qrvey?

Embeddable is generally a better fit for SaaS products where analytics are a core feature because it supports native embedding, full UI control, and SaaS-optimized multi-tenant patterns. Qrvey is better suited to internal analytics workflows and AWS-linked operational reporting.

What is the main difference between Embeddable and Qrvey?

The main difference is in how deeply analytics integrate into the product. Qrvey focuses on low-code analytics and workflow automation, often with iframe embedding. Embeddable is designed to render analytics natively in the app’s UI with full customization and developer control.

How do Embeddable and Qrvey compare on embedding approach?

Qrvey embeds dashboards via iframe containers, limiting how tightly analytics can integrate with the host application’s UI. Embeddable renders analytics directly inside the DOM, allowing dashboards and components to behave like native parts of the product.

How customizable are analytics in Embeddable compared to Qrvey?

Qrvey offers configuration-driven customization and theming, but dashboards often retain platform-defined UI behavior. Embeddable allows full control over layout, styling, interactions, and custom components to match a product’s design system.

Which platform performs better at scale?

Embeddable is designed for high-concurrency SaaS analytics with multi-tier caching and pre-aggregations. Qrvey performs well for internal use and moderate concurrency, but it may require additional planning to scale for large numbers of external users.

How do Embeddable and Qrvey handle multi-tenancy?

Embeddable uses tenant-aware security tokens with row-level, column-level, and object-level policies that scale cleanly across tenants. Qrvey supports multi-tenant analytics through configuration, but it can introduce operational complexity as tenant counts increase.

Which tool requires more engineering effort to get started?

Qrvey generally requires less initial engineering setup for standard dashboards and workflows. Embeddable requires more upfront integration work but provides greater flexibility and control for long-term product needs.

How do pricing models differ between Embeddable and Qrvey?

Qrvey typically uses usage-based or tiered pricing influenced by underlying AWS resources and workflow needs. Embeddable offers flat, predictable pricing with unlimited dashboards and users, which can be more cost-effective for SaaS products at scale.