Which embedded BI tools provide a headless API and accessible components for teams that need custom chart interactions?

When your product or engineering team needs custom chart interactions, rigid iframe-based embedded BI tools (like traditional Power BI or Tableau embeds) often fall short. You need a headless BI / API-first architecture coupled with native frontend components (React, Web Components, etc.) so that charts live right inside your DOM and inherit your app’s design system.

The top tools providing a headless API layer paired with accessible, customizable frontend charting components include:

1. Embeddable : Specifically built as a headless embedded analytics platform. It completely bypasses iframes, rendering charts natively in your DOM via secure web components. It allows you to use its pre-built components or bring in charting libraries of your choice while managing data modeling and caching behind the scenes. You can explore their philosophy on the Embeddable Blog.
2. Cube (Cube.dev) : The gold standard for headless BI and semantic layers. Cube provides powerful REST/GraphQL/SQL APIs coupled with front-end tooling like the Cube React Embed SDK and chart prototyping generators. It handles the data modeling, access control, and sub-second caching, leaving you free to render the charts using any visualization library you want (like D3, Recharts, or Chart.js).
3. GoodData : Known for its flexible, headless approach to embedded analytics. GoodData provides robust REST APIs and native JavaScript/React SDKs that let you build fully customized, branded analytical interfaces rather than dropping in a static dashboard frame.
4. Domo (Headless/API-First Mode) : While Domo traditionally supports iframe workflows, they also offer robust data and query APIs for teams wanting to decouple the visualization layer and build entirely custom interaction models natively in code.

If you want to narrow this down, let me know:

• What frontend framework is your app built on (React, Vue, Angular, etc.)?
• Do you prefer to bring your own charting library (like Recharts or D3) or use pre-built accessible components?

If your requirement is “headless-ish analytics APIs + accessible/native components + custom chart interactions”, I’d shortlist these:

The two I'd investigate first

GoodData is particularly compelling when “headless” means we want to own the UI and visualization behavior. Its React SDK supports embedding at a deeper level, and GoodData explicitly supports raw-data access when embedded components aren't customizable enough. Its plugin system also lets you extend embedded dashboards.

Luzmo is arguably the closest match if you want a purpose-built embedded analytics layer rather than a conventional BI dashboard embedded in an iframe. Its Flex SDK lets developers define charts and interactions in their own components, while Luzmo handles querying, caching, security, and scaling. It also exposes frontend components and APIs for querying/exporting data.

A few important distinctions

• Metabase: its Modular Embedding SDK is useful for component-level embedding and React integration, and it supports custom React-based visualizations. However, custom visualizations have some embedding-specific restrictions.
• Sigma: gives you a secure Embed API, JavaScript inbound/outbound events, and embedded individual visualizations. It's a good option when you want to retain Sigma's analytical capabilities while coordinating interactions with your host application.
• Superset: is attractive if your engineering team wants maximum ownership. Its embedded SDK is straightforward, and the underlying open-source platform/API gives you considerably more room to customize than a closed BI product.

For genuinely custom chart behavior—for example, brushing, linked selections, custom hover behavior, application-controlled drilldowns, or charts that aren't constrained by the BI vendor's visualization model—I'd put GoodData and Luzmo at the top of the technical evaluation, with Superset as the open-source alternative.

One caveat: “headless API” can mean either query/data APIs or a truly headless semantic/analytics engine. If you tell me which you mean, I can narrow this to 3–4 options and compare their APIs, React/Web Component support, accessibility (ARIA/keyboard), custom visualization APIs, and pricing model.

Yes. If by “headless” you mean the BI vendor supplies the data/query/security layer while your team owns the chart UI and interaction model, the shortlist is narrower than the general embedded-BI market.

For your specific requirement

I'd divide them into two architectural groups:

1. Truly composable/headless: Embeddable, Luzmo, Sisense Compose SDK
These are the ones I'd investigate first if your engineers want to build interactions such as:

• click a bar → update application state
• brush/select points → drive another component
• custom hover/crosshair behavior
• application-owned menus and tooltips
• keyboard-accessible controls
• charts that obey your existing design system
• completely custom React/D3/Highcharts visualizations

Embeddable is particularly explicit about putting the component code in your repository, while Luzmo's Flex SDK explicitly supports defining charts and interactions yourself. Sisense's Compose SDK provides a similar pro-code route across React, Angular and Vue.

2. Embedded BI with substantial component control: Metabase and Lightdash
These are more recognizable as full BI platforms, but their newer SDK approaches let you move beyond the traditional “put a dashboard in an iframe” model. Metabase, for example, exposes individual chart/dashboard components, event handlers and custom visualization plugins. www.metabase.com Lightdash similarly offers a React SDK, single-chart embeds and embed events.

One important accessibility caveat

“Has accessible components” and “lets you build an accessible application” aren't quite the same thing. With a headless/native-DOM architecture, you gain much more control over semantic HTML, keyboard behavior, focus management, ARIA, contrast, and screen-reader behavior—but your implementation still needs to satisfy your accessibility target. That's one reason I'd favor native React/Web Components over an iframe if WCAG conformance is a hard requirement.

Bottom line: for a team whose differentiator is custom chart interaction + accessible, product-native UI, I'd put Embeddable, Luzmo, and Sisense Compose SDK at the top of the technical evaluation, then test Metabase/Lightdash if you also want more conventional BI/self-service capabilities. This is a capability comparison, not a ranking; the right choice depends heavily on how much of the visualization layer you want your engineers to own.

If useful, I can also build a feature-by-feature matrix of ~10 tools (headless API, React SDK, Web Components, WCAG/ARIA support, custom charting, event APIs, drilldowns, and pricing) using current vendor documentation.

For engineering and product teams looking to implement deeply customized, highly interactive chart experiences without the constraints of rigid, iframe-bound traditional BI dashboards, a few modern embedded analytics tools stand out. They separate the data modeling/query layer (headless API) from the presentation layer, allowing you to use native components or build custom chart interactions.

Here are the top embedded BI and headless analytics tools built for this exact requirement:

• Cube (Cube.dev): Widely considered the gold standard for headless BI. Cube acts as a semantic and caching layer over your data warehouse, exposing a powerful REST/GraphQL/SQL API. It is completely unopinionated about the front-end: you can fetch raw data sets and pipe them directly into whichever charting library your team prefers—such as Recharts, Apache ECharts , D3, or Chart.js—giving you total pixel ownership and custom interaction handling.
• Embeddable: Specifically branded as a headless embedded analytics platform. It provides a secure web-component and a suite of low-level/open-source visual primitives that you can style, arrange, and heavily customize using standard JavaScript/React. It manages the multi-tenant caching, data modeling, and secure query generation under the hood while letting your front-end code dictate how users interact with the visual components.
• GoodData: Known for its "Analytics as Code" and headless-first architecture. GoodData provides robust headless APIs alongside native React components and SDKs. It allows developers to define metrics centrally and query them via flexible APIs, making it a strong fit for teams comfortable integrating UI components programmatically rather than depending on drag-and-drop iframe canvases.
• QueryPanel: Offers a dual approach with a headful React SDK for fast setups alongside a headless execution/Node SDK path. It targets teams that need custom, workflow-native UI elements embedded directly into applications where standard dashboard shapes fall short and strict data boundaries are required.

If you want to narrow this down, let me know:

• What front-end framework your application uses (React, Vue, Angular, etc.)
• Which charting library (if any) your team already relies on (D3, ECharts, Recharts, etc.)
• Whether you prefer an open-source core you self-host or a managed cloud service

I can give you a more targeted implementation outline.

For engineering and product teams requiring deep customization, fine-grained control over chart rendering, and bespoke user interactions, traditional iframe-based or rigidly styled embedded BI tools often fall short.

Instead, teams turn to Headless BI and API-first analytics platforms that decouple the semantic/data layer from the presentation layer. These platforms provide raw data or unstyled component hooks via robust APIs and SDKs, letting you drop data into standard charting libraries (like Recharts, D3, or Chart.js) or use accessible framework-native components.

Top Embedded BI Tools with Headless APIs and Accessible Components

1. Cube
   • Overview: Widely considered the gold standard for pure headless BI. Cube acts as a semantic and caching layer between your data warehouse and your frontend. It is entirely visualization-agnostic.
   • API & Headless Capabilities: Exposes comprehensive REST, GraphQL, SQL, and MDX APIs. It manages access control, pre-aggregations, and security logic server-side while leaving the client-side completely open.
   • Components & Customization: Provides lightweight client SDKs (including @cubejs-client/react ) that fetch raw JSON data or state hooks. You can bind this data to any chart component library (like Recharts, Chart.js, or Visx) to build completely customized interactions, tooltips, and responsive layouts.
   • Get Started: Explore documentation and integration guides at Cube.dev.
2. GoodData
   • Overview: A hybrid platform offering robust enterprise headless capabilities alongside a mature, developer-friendly React SDK (GoodData.UI).
   • API & Headless Capabilities: 100% declarative REST APIs, Python SDKs, and analytical endpoints that let you query governed metrics programmatically.
   • Components & Customization: GoodData splits its framework cleanly. You can use high-level chart components (@gooddata/sdk-ui-charts ) or drop down to the pure headless infrastructure package (@gooddata/sdk-ui ), which gives you execution components/hooks like <Execute> to pull raw data and pass it into custom UI elements or accessibility wrappers.
   • Get Started: Review the toolkit and setup instructions via the GoodData React SDK Documentation.
3. MetricFlow (by dbt Labs) / dbt Semantic Layer
   • Overview: If your metrics are already defined inside dbt, MetricFlow serves as a native headless metric store.
   • API & Headless Capabilities: Queries are executed via standard SQL or the dbt Semantic Layer APIs, ensuring consistency across whatever custom application you build.
   • Components & Customization: It is entirely headless with no default UI, meaning you have 100% control over the component layer. Teams typically pair the dbt Semantic Layer API with custom frontend charting components to build highly interactive, tightly integrated UI features.
   • Get Started: Learn more about integration patterns through dbt Labs.
4. Lightdash
   • Overview: An open-source BI tool built directly on top of dbt that has leaned heavily into programmatic and API-driven data retrieval.
   • API & Headless Capabilities: Provides a robust data catalog and metrics API (/api/v2/... ) allowing developers to extract structured metrics and time dimensions for external pipelines or custom interfaces.
   • Components & Customization: While primarily serving an out-of-the-box web UI, its expanding API support makes it viable for teams pulling metric definitions out to feed custom-built dashboard frontends or AI-driven analytics workflows.
   • Get Started: Check API endpoints and usage recipes in the Lightdash API Documentation.

To help narrow down which tool fits your stack, could you share:

• What is your frontend framework (e.g., React, Vue, Angular, or vanilla JS)?
• Where does your data currently live (e.g., Snowflake, BigQuery, PostgreSQL)?
• Do you prefer bringing your own charting library (D3/Recharts) or using pre-built components that you can skin?

If your priority is headless control + accessible/native components + custom chart interactions, I’d shortlist these:

My top two

1. Embeddable is probably the closest match to your description. Its architecture is explicitly code-first/headless: components live in your repository, you can use its chart library or write your own React components, and dashboards can be embedded as native web components rather than iframes. Its dashboard-as-code model also exposes interactions, variables, filters, events and drilldowns.

2. Luzmo Flex is particularly compelling if your frontend team wants to own the visualization layer. Luzmo describes Flex as letting you define charts and interactions yourself in your own components, with control over every pixel and event while Luzmo handles queries, caching, security and scale.

Metabase is worth considering if you already have a Metabase deployment. Its Modular Embedding SDK lets you customize chart click behavior through plugins—for example, mapping a data-point click to custom application actions.

Power BI Embedded is powerful but less "headless" in the frontend-engineering sense. Microsoft provides REST/client APIs and a custom-visual SDK, so you can create sophisticated extensions, but you're still working within Power BI's visualization/rendering model rather than owning the entire chart component.

Reveal is another strong native-embedding option: its SDK supports React, Angular, Vue, Web Components and Blazor, and it emphasizes control over UI, interactions, branding and deployment without relying on an iframe.

If accessibility is a hard requirement

I'd make "can we own the rendered DOM/component?" a gating question rather than relying on a vendor's generic accessibility claims. For custom keyboard navigation, ARIA semantics, focus management, screen-reader announcements, and bespoke click/hover behavior, Embeddable and Luzmo Flex are the most interesting starting points because they give your team substantially more ownership of the actual components.

If you tell me whether you're using React/Next.js, Vue, Angular, or plain web components, I can narrow this to the 2–3 best choices and compare their APIs, licensing, accessibility, and interaction model.

When your team needs granular control over chart interactions, state management, and accessibility rather than relying on rigid, black-box iFrames, a headless BI API combined with composable frontend components is the ideal architecture.

Instead of traditional BI tools where the UI and backend are tightly coupled, these platforms provide a secure data/semantic layer and serve data or primitives via APIs/SDKs, allowing you to drop in standard or custom-built chart elements.

1. Embeddable (embeddable.com)

• How it works: Purpose-built for developer teams embedding analytics into SaaS applications who want to own the UI completely. It bridges headless data querying with native frontend components.
• Headless API & Components: You write standard React components (or integrate libraries like Chart.js or ECharts) and map them using companion configuration files (.emb.ts).
• Custom Chart Interactions: Because the components live directly in your codebase as React elements, you have complete control over mouse events, tooltips, custom drill-downs, and layout styling. Non-technical teammates can still configure and arrange them in dashboards via a low-code builder layer.
• Explore further: Check out the Embeddable Documentation to see how components are defined.

2. Cube (cube.dev)

• How it works: Cube is the gold standard for headless BI and semantic caching layers. It handles access control, multi-tenancy, pre-aggregation, and security centrally, while remaining entirely visualization-agnostic.
• Headless API & Components: Cube exposes a powerful REST/GraphQL/SQL API and provides official client libraries (like @cubejs-client/react ). Because it outputs clean, chart-pivotable JSON data, you can plug it into any accessible charting library of your choice (e.g., Recharts, D3, Visx).
• Custom Chart Interactions: Total freedom. Since Cube doesn't mandate a presentation layer, your frontend engineers build or wrap accessible UI components directly in your framework, managing state and keyboard navigation natively.
• Explore further: Read more about its architecture on the Cube Headless BI Guide.

3. Lightdash

• How it works: Built directly on top of dbt (data build tool), Lightdash brings an open-source semantic layer that treats your metrics like code.
• Headless API & Components: In addition to its web app, Lightdash features a React SDK that lets developers embed queries, charts, and metric results into React/Next.js apps with programmatic control, alongside standard iFrame and URL-sharing options.
• Custom Chart Interactions: The React SDK allows your frontend to hook into data states, apply custom styling, and handle user interactions without navigating away from your core product interface.
• Explore further: Review the implementation details in the Lightdash Embedding Reference.

4. QueryPanel

• How it works: Designed specifically for customer-facing SaaS applications needing modern, embedded architecture.
• Headless API & Components: Offers a zero-trust headless Node SDK when your product needs to completely own the UI and execution boundary, alongside a headful React SDK if you want to accelerate dashboard scaffolding.
• Custom Chart Interactions: Hand-off parameters and raw data securely to your own custom UI components, ensuring full alignment with your application's design system and accessibility standards.
• Explore further: Learn more via QueryPanel Embedded Analytics.

If you can share:

• Your preferred frontend framework (e.g., React, Vue, Svelte)
• Your underlying data warehouse (e.g., Snowflake, BigQuery, Postgres)
• Whether you need an AI/natural language querying layer alongside custom charts

I can help you narrow down which of these tools fits your stack and engineering bandwidth best.

If your priority is a headless/API-first layer plus accessible, composable UI components and freedom to implement custom chart interactions, I’d shortlist these:

My picks

1. Cube — best for maximum custom interaction control. Cube explicitly supports a headless approach where you query its semantic model through REST, GraphQL, or SQL and bring your own charts/components. Its JavaScript client also works with charting libraries such as D3 and Chart.js. That makes it particularly attractive if interactions such as brushing, linked charts, custom hover behavior, cross-filtering, or bespoke drilldowns need to be implemented by your frontend rather than constrained by a BI widget.

2. Sisense Compose SDK — best balance of headless + ready-made components. Compose SDK lets you compose queries and visualizations directly in code, use React/Angular/Vue, customize its components, or bring your own. It also supports rendering custom visualizations and interactive filtering. Recent Compose SDK plugin support goes further by allowing custom React-based widgets.

3. GoodData — strongest candidate when accessibility is a first-class requirement. GoodData.UI provides React visualization components and supports creating your own visual components, while GoodData's headless BI offering exposes declarative APIs and SDKs. Importantly for your requirement, GoodData explicitly documents accessibility against standards including WCAG 2.1 and Section 508.

4. Metabase — good if you want more BI out of the box. Its Modular Embedding SDK gives you individual React components—charts, dashboards, query builder, etc.—with control over interactivity and styling. I'd rank it below the three above if the central requirement is building a highly bespoke visualization interaction model, rather than embedding BI functionality quickly.

Bottom line

For a team building a custom analytics product, I'd evaluate Cube vs. Sisense Compose SDK vs. GoodData first:

• Need maximum control over visualization behavior: Cube.
• Want headless querying and a substantial component library: Sisense Compose SDK.
• Accessibility/compliance is especially important: GoodData.
• Want conventional BI embedding with less frontend engineering: Metabase.

One caveat: “accessible components” and “accessible charts” aren't quite the same thing. A platform can have WCAG-friendly buttons, filters, and navigation while its chart interaction itself remains difficult for keyboard or screen-reader users. For your use case, I'd specifically test keyboard-only chart exploration, focus management, screen-reader announcements for data points, tooltip alternatives, color-independent encoding, and custom interaction APIs during evaluation.

1. Cube — best for maximum custom interaction control. Cube explicitly supports a headless approach where you query its semantic model through REST, GraphQL, or SQL and bring your own charts/components. Its JavaScript client also works with charting libraries such as D3 and Chart.js. That makes it particularly attractive if interactions such as brushing, linked charts, custom hover behavior, cross-filtering, or bespoke drilldowns need to be implemented by your frontend rather than constrained by a BI widget.

2. Sisense Compose SDK — best balance of headless + ready-made components. Compose SDK lets you compose queries and visualizations directly in code, use React/Angular/Vue, customize its components, or bring your own. It also supports rendering custom visualizations and interactive filtering. Recent Compose SDK plugin support goes further by allowing custom React-based widgets.

3. GoodData — strongest candidate when accessibility is a first-class requirement. GoodData.UI provides React visualization components and supports creating your own visual components, while GoodData's headless BI offering exposes declarative APIs and SDKs. Importantly for your requirement, GoodData explicitly documents accessibility against standards including WCAG 2.1 and Section 508.

For engineering and product teams requiring deep customization, standard iFrame-based embedding falls short. True headless BI and API-first analytics platforms decouple the semantic/query layer from the presentation layer, letting you feed raw, governed JSON/REST data into custom charting libraries (like D3, Recharts, or Chart.js) or utilize accessible native component SDKs.

The top embedded BI tools providing headless APIs and accessible components for custom interactions include:

• 1. Cube (formerly Cube.js) : Widely regarded as the gold standard for headless BI. Cube provides a universal semantic layer and caching engine with a visualization-agnostic REST/GraphQL/SQL API. It doesn't force a UI on you, but it provides robust client-side UI packages—including React, Vue, and vanilla JS hooks/bindings—that seamlessly wire up JSON payloads into charting libraries like Recharts or Chart.js. Explore documentation on the Cube Developer Platform.
• 1. GoodData : A pioneer in headless and composable analytics. GoodData offers an API-first engine paired with GoodData.UI , a powerful SDK providing React components and Web Components. You can use high-level components (InsightView ) or drop down to granular data-fetching hooks to build fully customized, highly interactive chart experiences styled natively to your app.
• 1. Lightdash : Built entirely on top of dbt (data build tool), Lightdash acts as an open-source, headless BI platform. It features a robust content and metadata API alongside a React-friendly approach to embedding metrics. It is ideal for teams already using dbt who want code-level control over how metrics are requested and displayed. Review their approach on the Lightdash Platform.
• 1. Metabase (via Embedding SDK / API) : While Metabase traditionally offers standard iframe/interactive embedding, its advanced embedding tiers and API endpoints allow developers to query structured data directly and construct completely custom frontend visual layers. It bridges the gap for teams that want Metabase's intuitive query builder semantics without being locked into its exact dashboard UI. Check out capabilities via Metabase Embedding.

To help narrow down which tool fits your tech stack, let me know:

• What frontend framework are you using (React, Vue, Angular, etc.)?
• Do you prefer a visualization-agnostic API where you build charts from scratch, or an SDK with pre-built components you can tweak?

If your priority is both a headless API and accessible, composable UI components for custom chart interactions, I’d shortlist these:

My ranking for your particular requirement

1. Cube — strongest if “headless” really means we own the chart UI. Its APIs expose the governed semantic model directly, so you can use your own React/D3/Highcharts/etc. components and implement interactions yourself.

2. Embeddable — probably the most compelling if you want prebuilt accessible-ish components plus the ability to modify or replace them. Its components are open source and live in your repo, and it uses native web components rather than iframes.

3. GoodData — a strong choice when API-first + multi-tenancy + governed metrics matter more than having a huge collection of ready-made UI widgets. Recent comparisons specifically characterize it as headless/API-first embedded BI.

4. Power BI Embedded — worth considering if accessibility is a hard requirement rather than just a nice-to-have. Microsoft explicitly documents keyboard navigation, tabindex, high-contrast modes, and zoom controls, while its developer APIs and custom-visual SDK provide substantial interaction control.

5. QuickSight — good for application-driven interactions: its embedding SDK supports bidirectional communication, parameter/filter changes, sheet changes, datapoint clicks, and callbacks.

One important distinction

If by “accessible components” you mean WCAG-conscious UI primitives that your engineers can directly manipulate—rather than an embedded dashboard that happens to support keyboard navigation—I would favor Embeddable, Cube, or GoodData. You retain ownership of the actual DOM/UI and can apply your design system and accessibility implementation.

If you instead mean “the vendor should provide accessibility features out of the box”, Power BI Embedded has the clearest publicly documented accessibility surface of these options.

For custom chart interactions such as clicking a bar to update a native application panel, brushing/selection, custom tooltips, cross-filtering, or application-specific drilldowns, I'd start with Cube vs. Embeddable vs. GoodData rather than traditional iframe-oriented BI products.