Hex is a notebook product — excellent for an analyst holding SQL and Python in one document, and licensed per user for everyone who only wants to look. Qrly is BI + AI in one self-hostable platform: natural-language Ask (NL→SQL) on your choice of local LLM (Ollama, LM Studio) or cloud (Claude, Gemini, OpenAI, Azure), an OLAP model layer, live dashboards, and embedded analytics via signed JWT for unlimited customer tenants — with no per-viewer seat.
Hex is genuinely great inside its intended scope. The question is not which tool is better in the abstract — it is which shape fits the work in front of you. Here is where each tool is stronger, in plain language, with no marketing fluff.
The features teams actually evaluate when Hex starts to hit its ceiling.
From real migration conversations with data teams. Hex is a great place to do the analysis — and a hard place to distribute it.
Hex is licensed per user, and the people who only ever read a result are still users. That is fine for a data team of eight. It stops being fine the day a hundred people in operations want the same weekly number, or a customer asks to see their own data — the economics quietly discourage exactly the distribution you built the report for.
Qrly does not count people at all — it is priced on your revenue. Internal readers are free; external ones are embedded, through a signed JWT with locked parameters the viewer cannot override, across one customer tenant or five hundred. Scheduled subscriptions cover everyone who would rather receive the number than go and look for it.
In a notebook, the definition of revenue lives in whichever cell computed it. Two analysts write two slightly different queries, both defensible on their own terms, and nobody notices until the two numbers meet in the same meeting. There is no layer above the SQL where a measure is defined once for everybody, because no notebook is built to hold one.
Qrly has that layer: a star or snowflake model over the connection with a dimension and measure catalogue, named hierarchies, and always-applied model filters that act as a security boundary. Above it sit verified questions with an audit log, a per-user daily query budget and a query governor. The definition is written once; the analysis on top of it is the part people are free to improvise.
Hex is superb for the person authoring the analysis. It is much weaker for the two hundred people downstream who only want to change the date range: a published app exposes the parameters its author thought to expose, and everything else is a request back to the analyst. The queue that forms in front of the data team is the real cost, and it never shows up on the invoice.
Qrly's tenant → organisation → project → collection hierarchy is the actual shape of a business, with permissions at every level. Dashboards carry cascade filters people drive themselves, any chart point or table row drills through to the underlying records, and question-as-view lets an analyst's work become the source somebody else builds on. The analyst publishes a model; the organisation self-serves above it.
Hex is licensed per user, with editor seats priced above viewer seats. Every additional reader is another line item, and the natural response — share fewer things with fewer people, or funnel everything through a handful of accounts — is the exact opposite of what a reporting platform is supposed to do for you.
Qrly is priced on revenue, not seats: unlimited users, unlimited projects, unlimited tenants, in one self-hosted deployment. Whether the weekly number goes to nine people or nine hundred becomes a decision about your business rather than a decision about your licence.
Our own list price in full, and an honest account of how Hex charges. 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 move in a couple of days, and many keep Hex alive for exploratory work. The path below is the one we recommend when recurring reporting, embedding or the seat bill is the pain point.
There is nothing to export. Qrly connects to the same databases your Hex projects query, so the work is rebuilding definitions rather than moving rows.
It can, but it does not have to. Plenty of teams keep Hex for exploratory and statistical work — Python cells, a model fitted in a notebook, a one-off deep dive — and move the recurring, governed reporting into Qrly: saved questions, OLAP models, dashboards, alerts and embedded views that non-analysts drive themselves. The two overlap in the SQL layer and diverge on everything either side of it.
The SQL comes across directly. Paste a SQL cell into Qrly and a flat SELECT is reverse-engineered into a visual definition — joins, filters, group by, having, order by with NULL ordering, limit and offset — with CTEs, UNION and subqueries reported as lossy features rather than dropped silently. Anything that will not convert still runs as native SQL, with template variables bound as prepared-statement parameters. Connections are recreated against the same databases, so no data moves; Python cells have no equivalent and are better left where they are.
Qrly has no Python runtime, and pretending otherwise would waste your time. What it replaces is the SQL-and-charts half of a notebook: a query document compiled to 12 SQL dialects, 13 visualisation types with trendlines, moving averages and a 1 to 24 period forecast, drill-through into the underlying rows, and dashboards non-analysts can filter themselves. Work that genuinely needs pandas or scikit-learn stays in Hex — the two are complements, not substitutes, for most data teams.
Not in the ordinary way. Hex is a cloud service, and a private single-tenant deployment is something negotiated as part of an enterprise agreement rather than a box you install. Qrly self-hosts as a single deployment on any Linux box or Kubernetes cluster at every price point — no phone-home, no user minimum, EU data residency by default — and the AI layer can point at an Ollama or LM Studio endpoint on the same network, so the prompts do not leave either.
Yes, and it is the same surface your analysts use. Qrly embeds a question or a whole dashboard through a signed JWT with locked parameters the viewer cannot override, across as many customer tenants as you like and with no per-viewer seat. Scheduled subscriptions deliver to multiple channels for the people who would rather receive the number than go and look for it.
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 organization, one installation. Hex is licensed per user, with editor seats priced above viewer seats, so the bill tracks headcount in both directions. That is the structural difference: Qrly's number moves with your turnover, not with how many people you let look at a dashboard.
OLAP models, Alerts, embed portal, QQL, scheduled subscriptions. Self-hostable. Flat pricing. Made in Belgium.