6 Best Data Visualization Tools for SaaS in 2026
Embedded data visualization is the charts, filters and drill-downs that appear inside a product's own screens, in the product's own design, showing each customer only their own data.
Unlike a separate analytics portal, it lets customers explore metrics while using the software, rather than exporting data or waiting for someone to prepare a report. A SaaS operations platform might display a chart of delivery times, let users filter it by location and drill down into individual shipments.
This is one part of embedded analytics, which also covers reporting, self-service exploration and the systems that make customer-facing analytics possible.
Here are six tools for bringing data visualization into a software product, and what each offers.
Embedded data visualization vs a standalone BI tool
A standalone BI tool shows data to analysts inside the vendor's own interface; embedded data visualization shows it to your customers inside yours.
The distinction affects more than where the charts appear. With embedded visualization, users work inside your product, follow its navigation and see only the data their account is permitted to access. Each customer's own data must remain separate, even when thousands of customers use the same application.
Choosing an appropriate visual still matters. A line chart may reveal a trend, while a scatter plot can show relationships between variables. Our guide to chart types explains which formats suit different questions, including specialized visuals such as a box plot.
Poor design can mislead regardless of how the chart is embedded. See these examples of bad data visualization for common mistakes.
What product teams need from embedded data visualization
Product teams need five things from embedded data visualization: charts inside the product, interaction, the product's own look, separate data for each customer, and code-level control when the standard charts fall short.
Charts inside the product. Users should encounter analytics where they already work. A customer reviewing orders shouldn't need to open another application to see order trends.
Interactive exploration. Useful charts allow customers to filter results, drill down into details and, where supported, change the chart type. A fixed image may communicate a single finding, but an interactive view can answer follow-up questions without another reporting request.
White-label embedding. Charts should match the application's typography, colors, layout and interaction patterns. Reporting becomes easier to navigate when it behaves like the surrounding product.
Multi-tenancy. Every customer must see only the data they're authorized to access. This requires more than a default dashboard filter. Permissions should remain effective when users change views or explore data. Our guide to multi-tenancy explains the underlying requirements.
Custom code when needed. Standard charts won't cover every product requirement. Some teams need specialized visualizations, SDKs or fully custom components, while others prefer low-code tools that reduce engineering work.
These capabilities should guide the selection process before a team starts implementing dashboards. Once you've chosen an approach, our guide to embed dashboards covers the practical integration steps.
1. Luzmo: embedded charts, dashboards and custom charts for product teams
Luzmo, the embedded analytics platform for product teams, gives you three ways to build the visual layer: a drag-and-drop dashboard editor with 40+ default chart types, custom charts you code, and components you compose in your front end.
Luzmo appears first because this is Luzmo's blog and product; the other five tools follow in no particular order. This list does not rank them.
Luzmo Studio
Luzmo Studio provides a dashboard editor with over 40 chart types, including interactive filtering and drill-downs.
According to Luzmo's embedded analytics product page, developers can embed dashboards using an iframe or web component, with SDK support for React, Vue and Angular.
The same page documents white-labeled themes, CSS injection and role-based permissions, allowing product teams to adapt the analytics interface to their applications.
Custom charts and Luzmo Flex
When standard charts aren't enough, custom charts let developers create visualizations using modern web technologies.
Luzmo handles data querying, filtering and permissions underneath. Custom visualizations can participate in existing filters, drill-downs and access controls rather than operating as isolated graphics.
Luzmo Flex offers another development approach. Teams can write charts in code or compose ready-made components, with both approaches using the same query, caching and security foundations.
Software engineer Sarah Nerby of Element Logic describes the flexibility as allowing her team to "go beyond the constraints of traditional dashboards." The full customer statement appears on Luzmo's custom charts page.
AI-assisted visualization
Luzmo also provides two distinct AI experiences.
Luzmo IQ offers AI-powered answers to users' data questions, including an embeddable assistant experience.
Luzmo AI supports generating visualizations from natural-language descriptions so they can appear within the application.
These capabilities complement the visual layer rather than replacing the underlying requirements for data access and permissions.
Pricing and product fit
As of October 2026, Luzmo offers one Embedded Everywhere plan starting at €1,995 per month, billed annually. Its model combines a fixed platform subscription with usage that scales alongside customer adoption.
White-label embedding, self-service, AI and APIs are included in the offering. See the current Luzmo pricing and white-label embedding pages for details.
Luzmo is not designed as a standalone reporting tool for analysts preparing their own internal reports. It is built for analytics your customers use inside your product.
2. Sisense: a code-first SDK
Sisense's Compose SDK is a code-first way to build analytics into your own app.
According to the Sisense Compose SDK documentation, it offers a composable approach to using Sisense platform capabilities within an application.
The documentation includes quickstart guides for React, Vue and Angular, and Sisense states that Compose SDK is available to all Sisense customers.
Developers can create queries, charts and filters in application code or render existing Sisense widgets.
See the Sisense comparison for more information.
3. ThoughtSpot: an embedded AI analyst
ThoughtSpot lets you embed its Spotter AI analyst inside your product.
According to ThoughtSpot's embedded analytics page, companies can embed Spotter as a white-labeled AI analyst or expose its agentic capabilities to their own agents through MCP and APIs.
ThoughtSpot describes these experiences as using a governed semantic layer to support data answers.
Our guide to ThoughtSpot provides additional context.
4. Metabase: low-code embedding or a modular SDK
Metabase gives you two ways to embed: low-code for speed, or the Modular Embedding SDK for more control.
According to Metabase's embedded analytics page, its low-code approach supports embedding charts and dashboards with customization options. Its Modular Embedding SDK for React provides greater control over component behavior, theming and interaction.
As of October 2026, the Metabase pricing page lists its Pro plan at $575 per month, or $517.50 per month billed annually.
The plan includes multi-tenant embedded analytics and is described as white-label ready. The first 10 users are included, after which Metabase charges $12 per additional user per month on monthly billing.
Metabase specifies that both internal team members and users accessing embedded analytics count toward its user-based pricing.
See the Metabase comparison.
5. GoodData.AI: workspaces, a semantic layer and SDKs
GoodData.AI prices embedded analytics by workspace and builds multi-tenancy into its workspace structure.
As of October 2026, the GoodData.AI pricing page describes its Professional plan as a platform fee plus a charge based on the number of workspaces, with unlimited users and data.
Professional includes full embedding, multi-tenancy and branding. GoodData.AI also documents hierarchical workspaces, a semantic layer and React and Python SDK support for generative AI.
For a closer comparison, see GoodData.AI.
6. Power BI Embedded: Power BI content inside your own app
Power BI Embedded lets software vendors put Power BI reports inside their own applications.
According to Microsoft Azure's Power BI Embedded page, developers can deliver branded, customer-facing reports using Power BI.
Microsoft advertises capacity-based pricing starting at $1 per hour, as of October 2026, with the ability to scale usage up or down and no separate end-user licensing required for the covered embedding scenario.
Microsoft also notes that creating the Power BI content being embedded may require additional Power BI Pro licenses.
Read more about Power BI Embedded.
How to pick the best data visualization for your product
Choose by answering six questions about your product, not by comparing feature lists.
- Will charts appear wherever users work? Can you place them within the existing interface rather than forcing customers into a separate reporting destination?
- Can users explore their own data? Look for filtering, drill-downs and controls appropriate to different roles.
- How much custom code or branding work is required? Consider the implementation effort needed to make the visualizations fit your application.
- Does it separate each customer's data? Check tenant-aware permissions across the full experience.
- Can business users build charts without developers? Determine whether the product needs self-service editing, developer-built views or both.
- Do the default chart types cover your requirements? If not, can the platform support custom charts without building an entire analytics foundation?
If you're weighing a visualization library against a complete embedded platform, our guide to Python chart libraries provides context on the library approach.
For a broader vendor selection, see our full comparison of embedded analytics tools.
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Bring data visualization into your product
Embedded data visualization works when the charts live where your customers already work, in your design, on their own data.
The six tools covered here offer different approaches to building that experience. The right choice depends on your product's architecture, the flexibility customers need and how much of the visualization layer your team wants to maintain.
Want to see embedded charts in your product?
FAQ
All your questions answered.
What should a data visualization tool offer a software product?
It should support charts embedded directly in the application, interactive filtering and drill-downs, branding that matches the host product and secure separation of each customer's data. Product teams should also consider how the visualizations integrate with the existing frontend and authentication system.
Can I add my own chart types to an embedded data visualization platform?
That depends on the platform. Luzmo, for example, supports custom charts built with modern web technologies. Developers create the visual components while Luzmo handles querying, filtering, permissions and dashboard integration. Custom charts can work alongside standard charts and participate in filters and drill-downs.
What should product teams consider when choosing a data visualization platform?
Start with integration requirements, scalability, customization and who needs to build dashboards. Some products need developer-controlled components, while others require business users to create their own visualizations. Check whether the available chart types cover your needs and whether tenant-aware security works throughout the embedded experience.
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