Qrly vs Hex
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.
Who wins where
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.
BI + AI in one self-hosted platform, flat pricing
- AI Ask (NL→SQL) across 12+ database dialects
- BYO LLM: local Ollama / LM Studio, or Claude / Gemini / OpenAI / Azure
- Embedded analytics via signed JWT — no per-viewer seats
- AI anomaly detection, schema descriptions, performance analyzer
- Multi-tenant hierarchy — tenant, organisation, project, collection
- Flat licence for unlimited users — editors and readers alike
SQL, charts and sharing the result
- Both write SQL against your existing databases
- Both chart a result and publish it for other people to read
- Both schedule refreshes and deliver results on a cadence
- Both expose an API and embed into your own application
The notebook, and what only a notebook does
- SQL cells and Python cells in one reactive document
- A free tier for individuals and small projects
- Hex Magic for AI-assisted authoring inside the notebook
- An app builder that turns a notebook into a shareable tool
- Fully managed — nothing for your team to run
Feature-by-feature comparison
The features teams actually evaluate when Hex starts to hit its ceiling.
| Feature | RecommendedQrlySelf-hosted · Belgium | HexCloud · notebook platform |
|---|---|---|
| Self-hostable on your own infra | Included | Private deployment on enterprise plans |
| No per-user licence counting | Included | Per user, editors and viewers |
| Built-in customer embed portal | Included | Embedded apps, no per-tenant portal |
| Alerts on saved questions (email, Slack, webhook) | Included | Scheduled runs with notifications |
| Native scheduled subscription (4 providers) | Included | Scheduled exports to email and Slack |
| Visual query builder and raw SQL, round-trip convertible | SQL ⇄ visual | SQL and Python cells, no visual spec |
| Azure AD + Google + LDAP + Basic simultaneously | Included | SAML SSO on enterprise plans |
| OIDC SSO user provisioning | Included | Enterprise tier only |
| AI with on-prem option (Ollama, LM Studio) | Included | Hex Magic is cloud-only |
| Multi-tenant architecture out of the box | Included | Workspaces, no tenant hierarchy |
| 40 connection types, 12 SQL dialects | Included | Broad warehouse connectors |
| Flat pricing (unlimited users) | Included | Per user, per month |
| Productive in under 5 minutes | Included | Hex is fast to start |
| EU data residency (native, not a tier) | Included | Vendor cloud; private deploy on enterprise |
| No add-on purchase required for the basics | Included | Key controls on enterprise plans |
| Dashboards with cascade filters and live push | Included | Notebook apps, not dashboards |
| REST API + webhooks | Included | Included |
| OLAP models with ROLLUP, CUBE, prior-period | Included | Write it in SQL; no model layer |
| Self-service for people who do not write code | Included | Authors write SQL or Python |
Four reasons teams outgrow Hex
From real migration conversations with data teams. Hex is a great place to do the analysis — and a hard place to distribute it.
Everybody who looks is a seat
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.
A notebook is not a governed model
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.
Notebooks scale to analysts, not to a company
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.
The bill grows with the audience
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.
Pricing, honestly
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.
Qrly
Annual licence · priced on your revenue · unlimited users, one organisation, one installation
- Annual licence at €15M revenue €6,300
- Per analyst / per viewer €0
- Per query, per credit, per capacity unit €0
- Embedded dashboard consumers €0
- Embedding, alerts, OIDC/SSO, row-level rules Included at every tier
- Self-hosting and bring-your-own LLM Included at every tier
Three years of licence: €18,900
That is our published schedule evaluated at €15M of revenue — 0.18% of the first €500k, then 0.12%, 0.0525% and 0.027% on each tranche above it. It does not move when you add users. The whole rate card, from the €900 floor upward, is on the pricing page.
Hex
Per seat, per month · a free tier, then published and quoted plans
- How it charges Per seat, per month
- Free tier Community use, limited
- Editor seats Priced above viewer seats
- Viewer and app-user seats Also licensed
- Private deployment Enterprise agreement, quoted
- List prices Published for the standard plans — check hex.tech/pricing
Hex’s meter is seats, and the seat count is what moves the moment a notebook turns into something the business reads every morning. That is the point at which the cost of Hex stops tracking the size of the data team and starts tracking the size of the company. Qrly’s licence tracks neither — it tracks turnover, once a year.
Moving from Hex to Qrly
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.
The standard migration path
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.
- Recreate the connections. Add each source in Qrly, test it before saving, then run a schema sync so the visual builder and the SQL autocomplete know the tables. Credentials are AES-encrypted at rest, execution limits are set per connection, and the pool hands out read-only connections.
- Paste the SQL cells in. 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. Anything that will not convert still runs as native SQL, with template variables bound as prepared-statement parameters.
- Define the model once. Where several projects recompute the same measures, build one OLAP model — fact table, dimension joins, a measure and dimension catalogue, named hierarchies — and everything above it inherits the definitions, the year-to-hour time drill, prior-period comparison and the always-applied model filters.
- Rebuild published apps as dashboards. Cards drop onto a 12-column grid with cascade filters mapped per card, live push on an interval or a Postgres LISTEN/NOTIFY channel, and signed-JWT embedding for anything customer-facing. Readers stop being seats.
- Keep Hex for what only Hex does. Python-heavy exploration, statistical work and one-off deep dives are worth keeping in a notebook. Move the recurring reporting — the queries that run every Monday for people who do not write SQL — into Qrly, and let the two live side by side.
Common questions
Does Qrly replace Hex for our analysts?
How do we move our Hex projects across?
What about our Python cells?
Can we run Hex on our own infrastructure?
Can we put a dashboard in front of our own customers?
Cost for 50 users over 3 years?
The full alternatives matrix
Evaluating Qrly against another tool? Jump to the detailed side-by-side.