QueryPanel vs Qrvey
Multi-tenant analytics automation for SaaS vendors.
Qrvey markets heavily to SaaS vendors embedding analytics. The platform bundles data workflows, visualization, and tenant-oriented packaging so teams can standardize on one vendor for customer analytics.
Last reviewed . Vendor facts are checked against public docs and pricing pages on that date.
Comparison at a glance
This table summarizes typical positioning. Every vendor changes over time—validate details against current documentation and your security review.
| Dimension | Qrvey | QueryPanel |
|---|---|---|
| In-app experience for end users | Web component widgets such as `<qrvey-dashboard>`, mounted in your page without iframes and authenticated with a backend-issued token; no React-specific package. | 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. |
| Platform shape | Bundled analytics platform aimed at SaaS embedding use cases. | Focused toolkit: React embeds + AI generation + optional headless `ask()` on your API, on top of your databases. |
| Trainable knowledge & steering | Knowledge is bundled with the vendor’s analytics pipeline; fine-grained SQL exemplars and column-level business notes next to your repo are less of a first-class workflow. | 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 | Self-hosted in your own AWS or Azure account on Kubernetes, with a managed data lake in your VPC or Live Connect to existing databases. | Designed so customer data stays in infrastructure you control; QueryPanel does not store warehouse passwords. |
| Customization | Configuration inside the vendor platform and standard embed patterns. | Code-adjacent: `@querypanel/react-sdk` for the dashboard shell, `@querypanel/node-sdk` in your middleware for signing and queries. |
| AI workflow | AI Chart Builder creates charts from prompts and the Sidekick assistant answers follow-ups; LLM options include OpenAI, Anthropic, Bedrock, or a model in your VPC. | Natural language is the default input for new charts in the embedded experience. |
| Multi-tenancy mechanism | Tenant scopes plus row, column, object, and feature-level policies carried in an encrypted token. | Tenant id in a short-lived RS256 JWT minted by `@querypanel/node-sdk`, applied during SQL generation. |
| End-user self-service | Tenant users can build dashboards and their own datasets through embedded builder widgets. | Tenants fork and customize dashboards in the Notion-like workspace and add charts by asking the AI assistant. |
| Pricing shape | Flat annual platform fee (Pro or Ultra), unlimited tenants and users, quoted by sales; you also pay to host it. | Tenant-based: unique tenants per billing month, not seats; AI chart generation metered separately; free tier. |
| Best first win | Standardize a single embedded vendor for many customer tenants. | Prove NL→SQL + one embedded dashboard in a single product area, then expand. |
A platform in your cloud versus a library in your app
Qrvey deploys as a containerized Kubernetes stack inside your own AWS or Azure account, with an optional managed data lake in your VPC or Live Connect to query existing databases. That keeps data in your cloud, but your team operates another platform. QueryPanel keeps data on your servers differently: SQL executes in your environment through the Node SDK, and there is no analytics stack to run. Ask who will patch, scale, and upgrade the platform before you choose.
Web component widgets versus React components
Qrvey embeds web component widgets, such as `<qrvey-dashboard>`, authenticated with a backend-issued token, and they work in any framework without iframes. QueryPanel ships React components: `QuerypanelEmbedded` renders the full dashboard workspace in your React tree, sharing your router, providers, and design tokens. For React teams the difference is about state, theming, and testing; for teams on several front-end frameworks, Qrvey's framework-neutral widgets can be the simpler choice.
Flat platform fee versus tenant-based pricing
Qrvey sells a flat annual platform fee with unlimited tenants, users, and dashboards, quoted by sales. That is predictable once you are large, but the entry price is a platform commitment. QueryPanel counts unique tenants per billing month, meters AI chart generation separately, and has a free tier, so cost tracks how many customers use analytics. Model both against your tenant count today and in two years.
When Qrvey is the better fit
Honest tradeoffs help your team pick faster—and match how buyers actually decide.
- You want a packaged embedded analytics suite with less custom glue between data prep and UI.
- You want the full analytics stack, including a data lake and transformations, deployed inside your own AWS or Azure account.
- You value automation-oriented features across the embedded lifecycle.
- Tenant users need to build their own datasets as well as dashboards, under one flat platform fee.
When QueryPanel is the better fit
Choose QueryPanel over Qrvey when you want a React-native dashboard workspace with an AI assistant on top of your existing database, without operating a full analytics platform in your cloud account. Keep Qrvey when you want a self-hosted, all-in-one stack with its own data lake, transformations, and tenant self-service under a flat fee.
- 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 customer UI as real React (`@querypanel/react-sdk`), not a set of third-party web component widgets, while keeping SQL execution and credentials on your servers.
- You want SQL generation and execution clearly separated: you run queries; QueryPanel never needs your warehouse passwords.
- You are optimizing for a developer-first integration: React in the browser, Node SDK in API routes, your auth model.
- You want AI-native flows (question → SQL → chart) wired directly into your product screens.
Pricing notes
Checked . Pricing changes; confirm on the vendor pages before you budget.
Qrvey
Qrvey does not publish list prices. Its pricing page describes a flat annual platform fee that is not charged per seat, per query, or per tenant, with unlimited tenants, users, and dashboards. There are two editions: Pro, and Ultra, which adds a data transformation layer, built-in data engine, and full-stack analytics. Both are quoted by sales, and the hosting cost of running Qrvey in your own cloud is on top.
QueryPanel
QueryPanel pricing is tenant-based: plans count unique tenants per billing month, not end-user seats. AI chart generation is metered separately, a free tier exists, and there is no analytics platform to host.
Sources: Qrvey pricing, QueryPanel pricing
Migrating from Qrvey to QueryPanel
1. Inventory widgets, datasets, and data flows
List every Qrvey widget you embed (dashboards, builders, reports), the datasets they read, and whether those datasets come from the Qrvey data lake or Live Connect. Datasets built through Qrvey transformations need a SQL equivalent in your database first.
2. Map Qrvey tenant scopes and security to a tenant claim
Write down the record-level security rules and tenant scopes in your Qrvey tokens. Map the tenant scope to the customer column in your database and have your backend mint a QueryPanel JWT with `@querypanel/node-sdk` that carries the tenant id, replacing the Qrvey token endpoint.
3. Sync the schema and add gold SQL
Run schema sync against the Postgres, ClickHouse, or BigQuery database. Turn the dataset logic customers depend on into gold SQL queries, add annotations for transformed or renamed columns, and add glossary entries for the metric names in your Qrvey dashboards.
4. Embed QuerypanelEmbedded on one route behind a flag
Install `@querypanel/react-sdk` and render `QuerypanelEmbedded` on one analytics route for internal accounts or a few pilot tenants, behind a feature flag. Keep the Qrvey web components on the existing route.
5. Compare numbers per tenant
For each pilot tenant, compare Qrvey charts with QueryPanel results for the same filters and periods. Gaps usually trace back to transformations in the Qrvey data pipeline; move that logic into views or gold SQL.
6. Cut over and shut down the Qrvey stack
Move tenants in batches, remove the Qrvey widget scripts and token service, then plan the shutdown of the Qrvey deployment, data lake, and sync jobs in your cloud account once no tenant reads from them.
Comparison FAQ
Is QueryPanel a good Qrvey alternative for a React SaaS product?
Yes, when you want analytics inside your React app on a database you already run, without hosting a separate analytics platform. QueryPanel's primary product is its headful React SDK with a Notion-like dashboard management system and AI assistant for tenant customization. Qrvey is the better fit when you want a self-hosted, full-stack platform with a data lake and dataset building.
Does Qrvey use iframes or React components?
Neither. As checked October 19, 2026, Qrvey embeds web component widgets such as `<qrvey-dashboard>`, authenticated with a token your backend issues, and it does not ship a React-specific package. QueryPanel ships `@querypanel/react-sdk`, whose `QuerypanelEmbedded` component renders inside your React tree.
How much does Qrvey cost compared with QueryPanel?
Qrvey does not publish list prices. Its pricing page describes a flat annual platform fee, not charged per seat, per query, or per tenant, with Pro and Ultra editions quoted by sales. QueryPanel pricing is tenant-based, counting unique tenants per billing month, with AI chart generation metered separately and a free tier.
How does Qrvey multi-tenancy compare with QueryPanel?
Qrvey defines tenant scopes plus row, column, object, and feature-level policies that travel in an encrypted token and apply across dashboards, reports, AI, and APIs. QueryPanel carries the tenant id in a short-lived JWT your backend signs with `@querypanel/node-sdk`, and applies it during SQL generation so every query is scoped to one customer before it runs.
Which AI features does Qrvey have, and how do they differ?
Qrvey offers an AI Chart Builder that creates visualizations from prompts and a Sidekick assistant, with a choice of LLM providers including a model running in your VPC. QueryPanel's AI assistant generates tenant-scoped SQL and charts inside the dashboard workspace, steered by gold SQL, annotations, glossary, and tenant definitions you train.
Is QueryPanel a full replacement for Qrvey?
Not if you use Qrvey's data lake, transformation layer, or tenant dataset building. QueryPanel does not ingest or transform data, is not a full BI suite, and does not focus on scheduled PDF reporting. It replaces the customer-facing dashboards and AI questions, reading directly from your Postgres, ClickHouse, or BigQuery database.
Related reading
- Metabase alternativesIncludes Qrvey as the self-hosted, flat-rate option for tenant self-service.
- Iframe vs native React embedded analyticsWeb components, React SDKs, and iframes compared.
- Embedded analytics for RLS and tenant isolationHow vendors keep one customer's rows away from another's.
- White-label embedded analytics for SaaSBranding, theming, and ownership trade-offs across vendors.
- QueryPanel Node SDK docs
Still evaluating Qrvey and QueryPanel?
Start on the free tier, embed one dashboard, and compare implementation time against your current shortlist.