Qrly vs Looker
BI + AI in one self-hosted platform — natural-language Ask (NL→SQL) and BYO LLM (local Ollama / LM Studio or Anthropic, Gemini, OpenAI, Azure) included by default. Looker is Google-Cloud-only, has no on-prem AI, and prices embedding as its own edition — Qrly runs on your infrastructure with embedded signed-JWT included, on one revenue-based licence.
Who wins where
No marketing fluff. Looker's developer experience is genuinely excellent and has set the bar for the whole category — here is where each tool is actually stronger when the dust settles and you look past the hero shots.
BI + AI in one self-hosted platform — flat pricing
- AI Ask (NL→SQL) with AI anomaly detection & schema descriptions
- BYO LLM — Anthropic, Gemini, OpenAI, Azure, or local Ollama / LM Studio
- Embedded analytics with signed-JWT included out of the box
- Full self-hosting (on-prem or private cloud) — not Google-Cloud-only
- Multi-tenant by design — tenant, organisation, project, collection
- Flat license — no per-seat scaling, EU data residency by default
Core analytics, APIs, SSO, dashboards
- Both build charts and dashboards on live warehouse data
- Both connect to BigQuery, Snowflake, Redshift and Postgres
- Both ship REST APIs and webhooks
- Both support SSO
- Both schedule and deliver reports
Semantic modelling, polish, ecosystem reach
- Genuinely exceptional UI and design polish
- LookML — a mature, governed semantic model
- Git-versioned model development with branches and review
- Mature native mobile apps
- Deep Slack and Google Workspace integrations
Feature-by-feature comparison
The features most teams actually evaluate when switching from Looker. Columns list the product as shipped — not as promised on a public roadmap.
| Feature | RecommendedQrlySelf-hosted · Belgium | LookerLooker |
|---|---|---|
| Self-hostable on your own infra | Included | SaaS-only, no on-prem |
| First query without building a model first | Included | Explores need LookML first |
| Built-in customer embed portal | Included | Signed embed URLs; the portal is yours to build |
| Alerts, anomaly detection and root-cause agent | Included | Threshold alerts on tiles |
| Scheduled subscriptions (PDF, CSV, inline) | Included | Email integration, limited |
| Visual query builder and raw SQL, round-trip convertible | SQL ⇄ visual | LookML compiles to SQL one-way |
| Azure AD + Google + LDAP + Basic simultaneously | Included | Cloud SAML only, no LDAP |
| OIDC SSO user provisioning | Included | Plus / Enterprise tier |
| AI with on-prem option (Ollama, LM Studio) | Included | Cloud AI only |
| Multi-tenant architecture out of the box | Included | Workspace per org |
| Connects to your existing warehouse on day 1 | 40 connection types | Native |
| Flat pricing (unlimited users) | Included | Per-seat, per-month |
| Productive in under 5 minutes | Included | Included |
| EU data residency (native, not a tier) | Included | Google Cloud regions, incl. EU |
| No marketplace plugin required for basics | Included | No marketplace, direct integrations |
| Dashboards, charts and scheduled reports | Included | Included |
| REST API + webhooks | Included | Included |
| Pivot tables and multi-level rollups | Included | Included |
| Markdown analysis documents included | Analysis reports | Markdown tiles on dashboards |
Four reasons teams leave Looker
From real migration conversations with engineering leaders and support directors. We are not arguing Looker is a bad product — it is a beautifully made one, and for pure internal data teams it is hard to beat on day-to-day feel. We are arguing it is missing specific things that a serious operations and customer-support stack needs, and those gaps are not easy to paper over with integrations.
Cloud-only is a dealbreaker for some
Regulated industries, government agencies, defense contractors, healthcare providers and organisations under EU-only compliance all need a self-host option. Looker has deliberately chosen not to offer one — there is no on-prem build, no private-cloud edition, no data-processing agreement that moves the data inside your own perimeter. That is a product philosophy choice, not an oversight, and it is internally consistent with Looker's engineering focus.
It is also, for a growing slice of the market, a hard stop. Qrly runs on your Linux server, in your VPC, or on your Kubernetes cluster. The data never leaves your infrastructure unless you decide it should, and the same binary runs in air-gapped environments.
Every new field goes through LookML
LookML is what makes Looker trustworthy, and it is also what makes it slow. A field that is not in the model does not exist: someone opens a branch, edits the LookML, gets it reviewed and deploys it before an analyst can group by it. That is excellent governance and genuinely poor turnaround, and it is why so many Looker shops still run a shadow layer of spreadsheets for the questions nobody wanted to file a merge request for.
Qrly puts the fast path first. An analyst builds the query visually or writes SQL, defines a calculated field from a SQL expression with server-side validation, and saves it — no branch, no deploy. Governance is available when it is wanted: an OLAP model with a dimension and measure catalogue, named hierarchies, and always-applied model filters that act as a security boundary, plus a verified-question badge with its own audit log.
Alerts only fire on numbers you already watch
A Looker alert is a threshold on a dashboard tile. It works, and it is the right tool when you already know which number matters and where the line sits. It does nothing at all about the metric nobody thought to put on a tile, which is reliably the one that moves the week before somebody notices.
Qrly ships the same threshold alerts — rows returned, goal reached, below goal, on an hourly, daily or weekly schedule, delivered to email, Slack or a webhook — and then adds the part that runs without being asked: nightly anomaly detection on recently used questions, an insights feed with trend-change, new-record, stale-data, correlation and seasonality detectors, and an Investigator agent that segments the anomaly and produces a structured root-cause document. Any insight is promoted to an alert in one dialog. All of it is in the core licence.
Per-seat pricing at scale
Looker charges a platform subscription and then a licence per person on top, split by role. That feels fair at twenty users and becomes a standing argument at two hundred, because growth itself turns into a line item — and the discussion about who really needs a seat starts competing with the discussion about what those people are doing with the data. We are not going to quote a euro figure at you; Google publishes the current one, and the shape of the model is the part that does not change.
Qrly's license is flat, tied to company revenue tier rather than headcount. The 201st user costs nothing. Neither does the 2,001st. Your analytics platform stops punishing you for hiring and starts behaving like infrastructure.
Pricing, honestly
Our own list price in full, and an honest account of how Looker 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.
Looker
Platform subscription plus per-user licences · Google Cloud
- How it charges A platform subscription, plus per-user licences on top
- User licences Developer, Standard and Viewer, priced differently
- Editions Standard, Enterprise and Embed
- Embedding Its own edition — priced apart from internal use
- Deployment Google Cloud only — no on-premise build
- List prices Standard published, Enterprise and Embed quoted — check cloud.google.com/looker/pricing
Looker’s embedding and its alerting are real and mature, and we are not going to pretend otherwise. The difference is not capability, it is what the meter counts: a platform fee plus a licence per person means every extra reader is a line item, and putting dashboards in front of your customers moves you onto a separate edition. Qrly charges once, on turnover, and never counts the person opening the dashboard.
Moving from Looker to Qrly
There is nothing to extract. Your numbers live in the warehouse, not in Looker, so a migration is a rebuild of the presentation layer rather than a data move — which is why most teams are cut over inside a working week, with a parallel-run period where both systems stay online for cautious users.
The standard migration path
Qrly connects to the same warehouse Looker queries — no third-party ETL, no paid connector, no export.
- Point Qrly at the same warehouse. BigQuery, Snowflake, Redshift, Postgres, MySQL, SQL Server — one of 40 connection types, read-only credentials, schema introspected on first sync.
- Rebuild the model. Explores that back real reporting become Qrly OLAP models — fact table, dimension joins, measure catalogue, named hierarchies and always-applied model filters. The modeller suggests candidates from the schema; a human approves or rejects them.
- Rebuild the Looks and dashboards. Most are faster to rebuild in the visual builder than to translate. For the awkward ones, paste the SQL Looker generated and Qrly reverse-engineers it into a visual definition, flagging CTEs, UNIONs and subqueries as lossy.
- Sync users via OIDC. Point Qrly at your identity provider (Okta, Entra ID, Google Workspace). Users keep their existing credentials and group memberships.
- Run in parallel if you want. Both tools read the same warehouse, so they can run side by side indefinitely. Reconcile the numbers, then decommission once no-one is opening Looker.
Common questions
Does Qrly have Looker's polished UX?
Can Qrly import my Looker data?
Can I self-host Qrly? (Looker cannot.)
What about LookML — do I lose the semantic model?
How does QQL compare to LookML and Explores?
How much is Qrly for 50 users over 3 years?
The full alternatives matrix
Evaluating Qrly against another tool? Jump to the detailed side-by-side.