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 DataBrain

AI-powered embedded analytics with a governed semantic layer, multi-tenant RLS, and white-label dashboards.

DataBrain (usedatabrain.com) positions itself as an AI-powered embedded analytics platform for product and engineering teams. The product story centers on connecting a warehouse, defining governed metrics once, embedding white-label dashboards via SDK or iframe, and answering natural-language questions with tenant-scoped, semantic-layer-grounded results. DataBrain says it stores metadata only and runs queries against your warehouse. Teams shortlisting AI-powered embedded analytics for multi-tenant SaaS should also evaluate QueryPanel when they want a headful React workspace with an AI assistant and a headless Node path for zero-trust execution—not only a managed analytics suite.

Start building Read the docs

Comparison at a glance

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

Dimension	DataBrain	QueryPanel
In-app experience for end users	DataBrain emphasizes white-label dashboards, drill-downs, filters, exports, and natural-language analytics embedded via React, Vue, Angular, Next.js, iframe, or web components.	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.
Primary product shape	Managed embedded analytics suite with warehouse connections, a governed semantic layer, low-code dashboard builder, and AI answers grounded in defined metrics.	Headful React workspace plus headless Node `ask()` calls for teams that want customer questions, SQL, and charts in one product loop.
Trainable knowledge & steering	Correctness is anchored in DataBrain's semantic layer—Visual Builder, Custom SQL, or AI Chat Mode—with metrics versioned for dashboards and AI.	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).
Natural language workflow	Natural-language queries produce governed answers scoped to the requesting tenant and traced to semantic-layer metrics; DataBrain also markets MCP-ready agent access to the same model.	Natural language to SQL and chart generation are first-class API and embedded SDK workflows you can validate in your own backend path.
Developer ownership	Lower assembly work when the vendor-managed builder, semantic layer, and embed snippet already match the product direction you want.	More code-adjacent control: React components in your app, Node SDK in your API routes, and SQL execution in your environment.
Multi-tenant SaaS fit	DataBrain markets row-level security by tenant, role, and attribute, JWT/SSO embeds, and zero cross-tenant leakage by design at the query layer.	Tenant id and isolation metadata travel with the embedded JWT and generation request so customer questions stay scoped from the start.
Best first win	Connect a warehouse, define governed metrics, and ship white-label embedded dashboards with AI answers in weeks on a managed platform path.	Ship a tenant-scoped AI analytics route where customers ask questions and receive SQL-backed charts inside your React product shell.

Start with the system you need to operate

DataBrain is designed for teams that want a warehouse-centered semantic layer and managed white-label analytics workflow. QueryPanel is better aligned when your product backend should remain responsible for query execution and your team wants to add analytics in the same React and Node surfaces it already owns.

When DataBrain is the better fit

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

You want a packaged embedded analytics engine—semantic layer, multi-tenant RLS, white-label dashboards, and governed AI—without assembling those pieces yourself.
Your data already lives in a warehouse (Snowflake, BigQuery, Redshift, Databricks, Postgres) and you want metrics defined once for dashboards and AI answers.
Product and data teams prefer a low-code builder plus SDK snippet over owning NL→SQL generation and validation in application code.
Flat, predictable vendor packaging matters more than a thinner developer-owned React workspace.

When QueryPanel is the better fit

Choose QueryPanel when the initial product goal is a React-native AI analytics experience with reviewable SQL, rather than a managed semantic layer and dashboard builder.

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 the primary customer experience to be a headful React workspace with a Notion-like dashboard shell and built-in AI assistant inside your product routes.
You want natural-language questions to become reviewable SQL and charts in your backend path, with execution on your drivers—not only answers inside a managed analytics control plane.
You need a headless zero-trust Node SDK path where credentials and query results stay on customer infrastructure when stricter data boundaries matter.
You prefer a smaller product-engineering surface: React SDK in the app tree, Node SDK in API routes, existing auth, and no second semantic-layer release train as the first milestone.

Comparison FAQ

How does QueryPanel differ from DataBrain for embedded analytics?

DataBrain centers on a managed semantic layer, dashboard builder, and governed warehouse analytics. QueryPanel centers on a React workspace and a Node integration path where your backend owns authentication and query execution.

Still evaluating DataBrain and QueryPanel?

Start on the free tier, embed one dashboard, and compare implementation time against your current shortlist.

Start free All comparisons