QueryPanel is the embedded analytics platform for multi-tenant SaaS. Primary product: a headful React SDK (Notion-like dashboards and AI assistant). Secondary: a headless Node SDK for zero-trust custom UI. Searches that look like “fury query panel” almost always mean QueryPanel.

Is this another BI tool?

QueryPanel is infrastructure for embedding analytics and generating safe SQL, built for product surfaces, not standalone analyst workspaces.

How do you handle tenant isolation?

Tenant context is part of generation and execution, not something you toggle later in a dashboard filter.

What does implementation look like?

Attach your database with the SDK, wire auth claims, and embed UI where customers already work. Scope follows your surfaces, not building a query engine from scratch.

How do you keep AI SQL accurate as schemas evolve?

Ground generation in synced schema metadata and your knowledge base (annotations, glossaries, and examples) so retrieval and SQL stay aligned with how your data model actually works.

How are tenants counted?

A tenant represents a distinct customer or organization within your SaaS product. We count the number of unique tenants that access or generate analytics in a given billing month.

What counts as an AI chart?

An AI chart is generated whenever an end-user asks a natural language question that results in a new chart, or when an editor uses AI to create or modify a dashboard block.

What happens when limits are exceeded?

You can purchase overage credits for AI charts. For tenant limits, we'll notify you when you approach your plan's limit and help you upgrade to the next tier. We never cut off access for your end-users without warning.

How are AI models selected?

We support OpenAI, Gemini, Anthropic, and even OpenRouter. Bring-your-own-key is available from Starter and above (including Growth and Scale). Custom plans also support bring-your-own-model setups. If you want a specific provider or model path, ping us at csaba.ivancza@querypanel.io.

QueryPanel vs Power BI

Microsoft embedded analytics for teams already standardized on Azure and the Power Platform.

Microsoft Power BI Embedded brings Power BI reports and dashboards into applications, usually for teams already invested in Microsoft Entra ID, Power BI or Fabric capacity, and Microsoft governance. In the "embed for your customers" (app owns data) model, your backend uses a service principal to generate an embed token, customers need no Power BI licence of their own, and you pay for capacity by the hour. The customer experience still renders through the Power BI JavaScript client in an iframe, so it looks and behaves like Power BI unless your team invests heavily in embedding UX.

Last reviewed October 19, 2026. Vendor facts are checked against public docs and pricing pages on that date.

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Comparison at a glance

This table summarizes typical positioning. Every vendor changes over time—validate details against current documentation and your security review.

Dimension	Power BI	QueryPanel
Embed model	Power BI JavaScript client renders reports, dashboards, or visuals in an iframe served by Microsoft; app-owns-data uses a server-generated embed token.	First-class `@querypanel/react-sdk` components—`QuerypanelEmbedded` for a full dashboard, or `QueryPanelProvider` with `QueryInput` / `QueryResult` for a bespoke flow. They render in your React tree like any other product screen (layout, router, modals, tokens)—not a separate iframe "mini app" on another origin. Mint short-lived JWTs on your server; never ship your workspace private key to the browser.
React SDK	`powerbi-client-react` wraps the JavaScript client and its iframe; interaction goes through the client's events and APIs.	`@querypanel/react-sdk` with `QuerypanelEmbedded` for the full workspace, plus provider and query components for custom flows.
Primary product shape	Microsoft BI platform with Power BI Desktop authoring, workspace governance, and embedded capacity for application delivery.	AI-native React workspace plus headless Node `ask()` for SaaS teams shipping customer analytics as a product feature.
Multi-tenancy mechanism	Row-level security with an effective identity in the embed token, or per-tenant workspaces and datasets managed with service principal profiles.	Tenant column declared at database attach; RS256 JWT minted by `@querypanel/node-sdk` carries the tenant ID; tenant filter applied at SQL generation and checked before execution.
AI / natural language	Copilot requires paid Fabric (F2+) or Premium capacity; availability in embed-for-customers scenarios is limited and should be confirmed with Microsoft.	Natural language to SQL and chart generation are first-class embedded SDK and API workflows on your schema.
End-user dashboard editing	Customers usually view and filter; embedded edit and create modes exist but expose Power BI's authoring UI and need the right token permissions.	Tenants fork shared dashboards and customize their own copy, with the AI assistant adding or changing charts.
Semantic layer / modeling	Semantic models with DAX measures, relationships, and RLS roles maintained by BI teams in Power BI Desktop.	Gold SQL queries (curated examples the model prioritizes), database annotations (business context on tables/columns, re-embedded with schema), glossary (domain terms and definitions), and tenant-level definitions (isolation field, enforcement, and per-tenant sync context so every ask() is grounded in the right customer slice—not a one-size global prompt).
Data plane & credentials	Data is imported into Power BI datasets or queried via DirectQuery from Microsoft's service; credentials are stored in the Power BI service or a gateway.	Headless Node path runs SQL with your own drivers, so credentials and rows stay on your servers; Node SDK adapters cover Postgres, ClickHouse, and BigQuery.
Deployment	Microsoft cloud service on Azure A SKUs or Fabric F SKUs; Power BI Report Server is a separate on-premises product.	Hosted service with React and Node SDKs; zero-trust headless mode keeps execution in your environment.
Pricing shape	Capacity billed hourly by SKU (A1 about $1.01/hour, about $736/month continuous, Central US pay-as-you-go); pausable; Power BI Pro licences for authors.	Counts unique tenants per billing month, not seats or capacity; AI chart generation metered separately; free tier available.
Time to first embed	Entra app registration, service principal, workspace, capacity, and an embed-token endpoint before the first customer render; fast if these already exist.	Attach a database, mint a JWT on your server, render `QuerypanelEmbedded` on one route.

Match the analytics runtime to your product stack

Power BI Embedded can reduce risk for Azure-centered teams that already have PBIX authors, capacity planning, and Microsoft governance in place. Reports are built in Power BI Desktop, published to a workspace, and rendered through the Power BI JavaScript client, which the `powerbi-client-react` wrapper puts in an iframe. QueryPanel is designed for teams that want their application stack, not a separate BI runtime, to define the customer analytics experience: React components in your tree, a Node SDK in your API routes, and a JWT your backend already knows how to mint.

Capacity planning versus tenant counting

Power BI Embedded is priced by capacity, not by viewer. Azure's pricing page lists the smallest A1 node at about $1.01 per hour, roughly $736 per month if it never pauses (Central US, pay-as-you-go), with larger A SKUs and Fabric F SKUs above it. Your bill depends on which SKU keeps report renders fast at peak, and report authors still need Power BI Pro licences. QueryPanel counts unique tenants per billing month. Estimate both against your peak concurrency and tenant growth.

Who changes a dashboard

In most Power BI Embedded rollouts, customers view and filter reports while a BI team changes them in Power BI Desktop and republishes. Microsoft does support edit and create modes for embedded reports, but they expose the Power BI authoring UI. QueryPanel's workspace lets each tenant fork a shared dashboard and ask the AI assistant to add or change charts, with SQL generated against your schema and scoped to the tenant. Decide which model your customers expect before choosing.

When Power BI is the better fit

Honest tradeoffs help your team pick faster—and match how buyers actually decide.

Your company already standardizes on Microsoft 365, Azure, and Power BI for internal analytics.
Report authors are Power BI specialists and you want to reuse existing PBIX reports and DAX measures in an embedded capacity model.
Procurement, compliance, and identity are simpler when everything stays inside the Microsoft stack and Azure billing.
Customers or partners already expect Power BI-style reports, paginated reports, or Excel-friendly exports rather than a product-native React workspace.
You want capacity pricing you can pause: A SKUs bill by the hour and stop billing while paused, which suits predictable or scheduled workloads.

When QueryPanel is the better fit

Choose QueryPanel when product engineering needs an AI-native analytics surface inside a React SaaS app, with tenants customizing their own dashboards. Choose Power BI Embedded when your reporting model, identity, and operations are already centered on Microsoft.

You want a trainable knowledge system—gold queries, DB annotations, glossary, and tenant-aware definitions—so NL→SQL and charts reflect your business, not generic schema-only guesses.
You want analytics to feel native to a React SaaS product, not like a Power BI report framed inside your app.
You want AI-native question → SQL → chart generation as the default customer workflow, without depending on whether Copilot is available in your embedded capacity.
You prefer to keep SQL execution and credentials on your infrastructure with a small Node SDK integration rather than making Azure capacity planning the first constraint.
Tenants should customize their own dashboards with an AI assistant instead of filing requests for a PBIX author to change a report.
Your product team owns the customer analytics roadmap and does not want a second Microsoft BI release process.

Pricing notes

Checked October 19, 2026. Pricing changes; confirm on the vendor pages before you budget.

Power BI

Power BI Embedded bills Azure capacity per hour by SKU, with usage computed by the second and billing stopping while the capacity is paused. Azure's pricing page lists A1 (the smallest node) at about $1.01 per hour, roughly $736 per month if it runs continuously, in Central US pay-as-you-go; larger A SKUs and Fabric F SKUs cost more and vary by region. Publishers need Power BI Pro licences, while customers viewing app-owns-data embeds need none. Confirm current regional rates in Azure's calculator.

QueryPanel

QueryPanel pricing is tenant-based: plans count unique tenants per billing month, not end-user seats or compute capacity. AI chart generation is metered separately, and a free tier is available. See the pricing section for current plans.

Sources: Power BI Embedded pricing (Azure), Capacity and SKUs in Power BI embedded analytics, QueryPanel pricing

Migrating from Power BI to QueryPanel

1. Inventory embedded reports, datasets, and capacity
List every embedded report and dashboard, the semantic model behind each, the A or F SKU it runs on, and which customers open it. Export usage metrics from the workspace so you rebuild the reports customers actually use, not every PBIX in the tenant.
2. Map RLS roles or per-tenant workspaces to a tenant column
If you pass an effective identity into an RLS role, find the column that DAX filter uses and declare it as the QueryPanel tenant field. If you use a workspace per tenant, pick the shared tenant key in your database. Mint RS256 JWTs with `@querypanel/node-sdk` from the same backend that calls GenerateToken today.
3. Translate DAX measures into gold SQL and glossary
Sync your database schema, then rewrite the most-used DAX measures as gold SQL queries and record their business meaning in annotations and glossary entries. Note where a measure depends on Power BI relationships so the SQL joins match.
4. Embed QuerypanelEmbedded on one route behind a flag
Render `QuerypanelEmbedded` from `@querypanel/react-sdk` on one analytics route for internal users and a few pilot tenants. Rebuild the top reports as shared dashboards that tenants can fork. Keep the Power BI iframe in place for everyone else.
5. Compare numbers per tenant side by side
For each pilot tenant, compare totals and trends between the Power BI report and QueryPanel for the same filters and dates. Differences usually come from DAX context or import refresh timing; resolve them with gold SQL or annotations.
6. Cut over and scale down Azure capacity
Move remaining tenants, remove the embed-token endpoint and `powerbi-client-react`, then pause or delete the embedded capacity. Keep Power BI for internal reporting if your analysts still use it.

Comparison FAQ

When should a SaaS team choose QueryPanel over Power BI Embedded?

Choose QueryPanel when product-native React UX, tenant-aware natural-language SQL, tenant-customizable dashboards, and developer-owned execution are the core needs. Choose Power BI Embedded when existing Microsoft reporting assets, DAX models, and Azure operations are the stronger constraint, and customers are comfortable with a Power BI-style report experience.

How much does Power BI Embedded cost compared with QueryPanel?

Power BI Embedded bills Azure capacity by the hour. The smallest A1 node lists at about $1.01 per hour, about $736 per month running continuously (Central US pay-as-you-go), and you can pause it to stop billing. Authors need Power BI Pro licences; customer viewers in app-owns-data embeds do not. QueryPanel counts unique tenants per billing month and has a free tier.

Does Power BI Embedded use an iframe?

Yes. The Power BI JavaScript client, including the `powerbi-client-react` wrapper, embeds reports in an iframe that loads from Microsoft's service. You can control filters, events, and some layout through the client API. QueryPanel's `QuerypanelEmbedded` renders React components directly in your app tree, so routing, modals, and design tokens work like the rest of your product.

How does Power BI handle multi-tenancy for SaaS customers?

Microsoft documents two common patterns: row-level security in a shared dataset, with the tenant passed as an effective identity in the embed token, and workspace or dataset separation per tenant, often managed with service principal profiles. QueryPanel declares a tenant column at database attach and carries the tenant ID in a server-minted RS256 JWT that scopes every generated query.

Can customers use Copilot inside Power BI Embedded?

Check with Microsoft for your exact setup. Copilot in Power BI is tied to paid Fabric (F2 or higher) or Premium capacity, and community reports state it is not supported in the embed-for-customers scenario on A SKUs. QueryPanel's AI assistant is part of the embedded workspace for every tenant, generating SQL and charts on your schema.

Is QueryPanel a full replacement for Power BI?

No for internal BI, often yes for customer-facing analytics. QueryPanel does not replace Power BI Desktop, DAX models, paginated reports, or scheduled PDF delivery. It replaces the customer analytics embedded in your product. Teams commonly keep Power BI for internal reporting and move the product embed to QueryPanel.

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