MongoDB Charts vs Metabase vs Knowi: Which Is Best for Embedded Analytics?

TL;DR

If you’re building a SaaS product on MongoDB and need to embed analytics inside your application, you’ll run into the same shortlist:

• MongoDB Charts – Native to Atlas, free to start
• Metabase – Open source, flexible, developer-friendly
• Knowi – Purpose-built for embedded analytics

All three can visualize MongoDB data. But once analytics become customer-facing, the differences matter more than chart types and filter options. If you’re still evaluating whether to build or buy embedded analytics, start there first.

This guide compares MongoDB Charts vs Metabase vs Knowi specifically for embedded analytics, where each tool fits, where each breaks down, and how to choose based on where your product is headed.

Building customer-facing analytics on MongoDB?

See how teams implement secure, multi-tenant embedded analytics without rebuilding later.

Explore embedded analytics with Knowi.

Table of Contents

Why Embedded Analytics Is Different from Internal BI

Most teams start thinking: “We just need some charts inside our app.”

Then reality hits.

Embedded analytics introduces requirements that internal BI tools weren’t designed for:

• Multi-tenant data isolation – Each customer sees only their data

• Authentication integration – SSO tied to your app’s user system (see SSO vs Secure URL Embedding for tradeoffs)

• White-labeling – Charts that look like your product, not a third-party tool (our White-Label Embedded Analytics Guide covers this in depth)

• Performance isolation – One customer’s queries can’t slow down others

• Operational simplicity – Fewer moving parts as you scale

Tools built for internal analytics often struggle when moved into customer-facing environments, a pattern we break down in Why Embedded Analytics Fails Without a Data Layer. That’s where MongoDB Charts, Metabase, and Knowi diverge.

In practice, most SaaS teams begin with MongoDB Charts or Metabase for internal reporting. The shift typically happens when analytics becomes a customer-facing product feature, at which point security, multi-tenancy, and scalability requirements start to outweigh convenience.

Side-by-Side Comparison

Before choosing an embedded analytics tool, make sure it supports:

• Native multi-tenancy (not just injected filters)

• Secure SSO tied to your app’s users

• Full white-label control without CSS hacks

• Predictable pricing as customers scale

• Cross-source analytics if your product requires it

MongoDB Charts: Native to Atlas, More Capable Than It Looks

Where it works well

• Internal dashboards for engineering or ops teams

• Teams fully committed to MongoDB Atlas

• Quick visualizations without additional infrastructure

• Prototyping before committing to a dedicated solution

Embedding capabilities

MongoDB Charts offers two embedding approaches:

1. iframe embedding – Simple but limited to unauthenticated charts

2. Embedding SDK – Supports authenticated embedding with Google, JWT, or custom authentication providers

The SDK also supports injected filters, which let you pass user-specific parameters to filter data at render time. This is the foundation for building multi-tenant views but you’ll implement the logic yourself.

Where it gets difficult for embedded analytics

• Multi-tenancy is manual – You must enforce tenant isolation via filters

• White-labeling is limited – Styling control exists, but deep branding is difficult

• Atlas-locked – No joins with PostgreSQL, REST APIs, etc. (see How to Join MongoDB Data with MySQL, Elasticsearch, REST APIs for what’s possible with federation)

• No row-level security model – Security depends on your implementation

Verdict

MongoDB Charts is more capable than “just iframes”, the SDK enables authenticated embedding and user-specific filtering.
But for production multi-tenant SaaS, you’ll be building the tenant model, security layer, and branding yourself.

Good for: Internal dashboards, early prototypes

Challenging for: Customer-facing analytics at scale

For a deeper look at MongoDB Charts’ capabilities and limitations, see MongoDB Charts: What It Is, How It Works, And What It’s Used For.

Metabase: Flexible, Powerful, and Now with a React SDK

Where it works well

• Teams with engineering capacity who want control

• Internal analytics with complex requirements

• Organizations that prefer open-source and self-hosting

• Products where analytics is a feature, not the core value prop

Embedding capabilities

Metabase supports:

1. Static embedding – Signed iframes (read-only)

2. Interactive embedding – Drilldowns and filtering (Pro tier)

3. React SDK – Modular components for deeper integration

Pro tier ($500/month for 10 users) includes:

• Interactive embedding

• Row- and column-level permissions

• SAML SSO

• Partial white-labeling

Where it gets difficult for embedded analytics

• Multi-tenancy requires work – No native tenant model

• Costs scale with users – $10/user/month adds up fast

• You own infrastructure – Hosting, scaling, upgrades, security

• White-labeling is partial – Full control often requires Enterprise

The real cost calculation

Verdict

Metabase is a legitimate embedded analytics option, especially with the React SDK.
But costs scale linearly with users and require ongoing engineering investment.

Good for: Technical teams, moderate scale
Challenging for: High-volume customer-facing analytics

Knowi: Built for Embedded Analytics from Day One

Where it works well

• SaaS products with customer-facing analytics

• Multi-tenant environments with strict data isolation

• Teams that need to ship quickly

• Cross-source analytics (MongoDB + SQL + APIs)

Embedding capabilities

• Native multi-tenancy

• Secure iframe, JavaScript SDK, or API embedding

• Built-in SSO, RBAC, row-level security

• Full white-labeling (themes, CSS, branding removal)

• Cross-source joins without ETL (learn how in Embedded Analytics Architecture for SaaS)

What Knowi doesn’t do well

• Overkill for internal dashboards

• No public pricing

• Smaller community ecosystem

• More upfront configuration options

Verdict

Knowi fits when embedded analytics is a product feature, not an internal tool.
You trade open-source flexibility for speed, security, and lower engineering overhead.

Good for: Customer-facing SaaS analytics

Challenging for: Internal-only or budget-constrained teams

For a full walkthrough, see The Complete Guide to Embedded Analytics with Knowi.

Decision Framework

The Hidden Costs of “Free”

“Free” tools aren’t free once you factor in engineering time and scaling.

Frequently Asked Questions

Summary

MongoDB Charts

• Strengths: Free, Atlas-native, SDK

• Weaknesses: Manual multi-tenancy, limited white-label

• Best for: Internal dashboards

Metabase

• Strengths: Open-source, React SDK, strong community

• Weaknesses: Per-user pricing, infra ownership

• Best for: Technical teams at moderate scale

Knowi

• Strengths: Native multi-tenancy, full white-label, cross-source joins

• Weaknesses: No public pricing, smaller community

• Best for: Customer-facing SaaS analytics

Most teams don’t choose the wrong tool, they choose the right tool for the wrong stage.

The real question isn’t “Which tool has the best charts?”
It’s “What’s the total cost, in dollars and engineering time, to make this production-ready for customers?”

Building customer-facing analytics on MongoDB?
See how Knowi handles multi-tenant embedding

Related Resources

• MongoDB Analytics Made Easy with Knowi: A Step-by-Step Guide
• Is MongoDB Good for Analytics?
• Challenges of Traditional MongoDB Analytics
• Best Embedded Analytics Tools 2025
• MongoDB Analytics: Solutions & Best Practices
• The Best MongoDB Visualization, Reporting and Analytics Tools