Qrly is the self-hostable BI + AI platform Redash never became — a stagnant OSS project since the Databricks acquisition, with no AI Ask, no anomaly detection and no enterprise plumbing. Qrly ships natural-language Ask (NL→SQL), AI anomaly detection and BYO LLM (local Ollama / LM Studio or cloud Claude, Gemini, OpenAI, Azure) alongside QQL across 12+ dialects, embedded analytics with signed-JWT, OIDC SSO and flat pricing for unlimited users.
No marketing fluff. Redash is a genuinely great product — here is where the two tools diverge.
The features most teams actually evaluate when Redash starts to creak.
From real migration conversations with ops and engineering leaders.
Redash does one thing: you write SQL, it runs it, you pin the result on a dashboard. There is no modelling layer, no visual query builder and no reusable metric definition, so the same revenue calculation gets retyped in fourteen queries and drifts in nine of them. Everybody who wants a number either writes SQL or queues behind somebody who can.
Teams paper over it by copying an existing query and editing it, which is how an instance ends up with nine hundred queries and no idea which four matter. Rename a column in the warehouse and an unknown number of them break, quietly, in whichever dashboard somebody opens next.
Qrly keeps the raw-SQL path exactly as it is — Monaco, schema-aware autocomplete, EXPLAIN — and puts a visual query builder, calculated fields, question-as-view and OLAP models beside it. A flat SELECT converts into a visual definition, so SQL is a starting point rather than a permanent dependency.
Redash development has been largely dormant since the Databricks acquisition. Releases are rare and the capabilities a modern BI stack is expected to have — a semantic layer, AI assistance, governed metrics, embedded analytics with per-viewer scoping — are not arriving, because there is no roadmap for them to arrive on.
That is survivable while Redash keeps doing the one job it is good at. It stops being survivable the moment a database driver, an auth requirement or a compliance rule moves on and the upstream project does not move with it. At that point the maintenance is yours.
Qrly is actively developed, compiles to 12 SQL dialects across 40 connection types, and comes from one vendor with one contract, one upgrade path and one support line.
Self-hosting is the one thing Redash genuinely gives you: Docker, your server, your data. What it does not give you is the scaffolding around it — no OIDC provisioning, no SCIM, no per-user query budget, no query governor, no read-only guarantee beyond the database user you remembered to configure, and no on-prem AI because there is no AI at all.
For a regulated team — finance, health, public sector, defence suppliers, anyone with DORA, NIS2 or a sovereign-cloud clause — the DPO conversation is fine and the security review is not. Every control the auditor asks about has to be built around Redash rather than found inside it.
Qrly self-hosts on any Linux box or Kubernetes cluster and brings the controls with it: OIDC SSO, a sanitizer that accepts SELECT and WITH only, read-only pooled connections, per-user daily query budgets, a query governor, and AI running locally through Ollama or LM Studio so prompts never leave the perimeter.
Customer-facing analytics — per-tenant scoping, signed tokens, locked parameters, a portal your customers log into — is not something Redash attempts. A public dashboard link is the extent of it, and a public link is exactly what you cannot hand a customer when somebody else's data is one filter away.
In practice teams that need it bolt a second product alongside Redash — two tools, two bills, two data models, and every metric defined twice, differently, by two teams who never compare notes until a customer does it for them.
Qrly ships embedding with signed JWT and locked parameters, multi-tenant separation from Tenant down to Collection, dashboard cascade filters where a viewer may only supply a filter id and a value, and scheduled subscriptions — in the same product that runs your internal dashboards, with one audit trail and one permission model.
Our own list price in full, and an honest account of what Redash actually costs to run, given that nobody sells it. The Qrly column is the published schedule evaluated at €15M of revenue — the number of people using it does not move it.
Methodology, 28 August 2026. Qrly publishes a complete rate card, so the figures in our column are quoted exactly. The other column describes a pricing model rather than quoting a number: vendor list prices change without notice and several of these vendors do not publish one at all. For current figures, go to the vendor’s own pricing page.
Most teams are up and running on Qrly within a working week.
A Redash query is SQL text, and that is essentially the whole migration. Pull the queries out through the REST API, point Qrly at the same data sources, and paste. No third-party ETL step, no paid migration consultant, no scripting weekend.
Yes — that is exactly the gap Qrly fills. Redash is excellent at one thing: writing raw SQL against a data source and pinning the result on a dashboard, and we would never argue otherwise. There is no modelling layer, no visual query builder and no AI, and the project has been largely dormant since the Databricks acquisition. Qrly picks up where that stops — a visual query builder compiling to 12 SQL dialects, OLAP models, embedded analytics behind signed JWT, OIDC SSO and multi-tenancy — while keeping the raw-SQL path exactly as you use it today.
Yes, and the move is unusually clean because a Redash query is just SQL text. Pull the queries through the Redash REST API with an API key, point Qrly at the same data source, and paste the SQL into Qrly's native editor. Redash parameters become Qrly template variables bound as prepared-statement parameters rather than substituted into the string, and any flat SELECT reverse-engineers into a visual QQL definition, with CTEs, UNION and subqueries flagged as lossy and left as native SQL. Nothing is trapped in a proprietary format, which is the one real advantage of a tool built on raw SQL.
They rebuild quickly, because the queries underneath them come across unchanged. Redash dashboard widgets become Qrly dashboard cards on a 12-column grid, with cascade filters mapped per card, live push over WebSocket or PostgreSQL LISTEN/NOTIFY, and scheduled subscriptions to several channels. A Redash alert on a query result maps onto a Qrly alert with multi-channel delivery. What you gain in the rebuild is everything Redash leaves on the table: 13 visualisation types, trendlines, moving averages, forecasts, conditional formatting and drill-down from a chart point to the underlying rows.
Redash stops where raw SQL stops. There is no modelling layer, no visual builder for the people who do not write SQL, no OLAP rollup or period-over-period comparison, no drill-down, no signed-JWT embedding for customers and no multi-tenancy — and development has been largely dormant since the Databricks acquisition, so none of it is arriving. Teams either accept a permanent SQL bottleneck, where every question queues behind the two people who can answer it, or they move to a platform that covers it natively. The second option is usually cheaper and definitely less fragile.
Yes, and then some. Writing raw SQL against a connection and pinning the result on a dashboard works the same way it does today, in a Monaco editor that adds schema-aware autocomplete, EXPLAIN and an AI explain. The difference is what happens next: a flat SELECT converts into the visual builder, drill-down works on the result, and 13 visualisation types with trendlines, moving averages and forecasts are there without a plugin. Nothing about the fast path gets slower — Ctrl+Enter still runs the query.
Qrly is priced on revenue, not seats: a €15M-revenue company pays €6,300 a year — €18,900 over three years — for unlimited everything, one organisation, one installation. Redash is open source and self-managed, and the project publishes no commercial plans, so there is no vendor number to set beside that. Its cost is entirely operational — the servers, the upgrades and the engineer who owns them — plus whatever you end up building or doing without. We are not attaching a euro figure to that; it depends on your team’s rate, not on ours. Our number does not grow when you hire the 51st person.
Self-hostable. Flat pricing. The raw SQL you already write, with the platform Redash never built around it. Made in Belgium.