BI + AI · Mode Alternative

Qrly vs Mode

Mode (now part of ThoughtSpot) is a SQL-and-notebook workbench — it has report alerts and white-label embeds, but not a governed BI layer, and its roadmap now sits inside ThoughtSpot's. 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), live dashboards, multi-channel alerts, and embedded analytics via signed-JWT.

Qrly wins

BI + AI in one self-hosted platform, flat pricing

  • AI Ask (NL→SQL) — Mode has no native NL→SQL workflow
  • BYO LLM: local Ollama / LM Studio, or Claude / Gemini / OpenAI / Azure
  • Embedded analytics with signed-JWT and a per-tenant portal, in the base licence
  • Multi-channel alerts with escalation — email, Slack and webhook
  • AI anomaly detection, schema descriptions, performance analyzer
  • Self-hosting, multi-tenant, flat pricing — independent of ThoughtSpot
Tie / depends

UI polish, SQL editing, API, integrations

  • Both have clean, modern UIs
  • Both give analysts a first-class SQL editor
  • Both expose a REST API for automation
  • Both integrate with Slack and common IdPs
  • Both schedule report delivery by email
Mode wins

Notebooks & analyst-led exploration

  • Python and R cells alongside SQL in one document
  • Visual Explorer iterates charts fast on a result set
  • Strong fit for one-off, exploratory analysis
  • Nothing to run — fully managed SaaS
  • Analysts already know the notebook workflow
Feature
Recommended Qrly Self-hosted · Belgium
Mode Mode
Self-hostable on your own infra
Included
SaaS only
Visual query builder for non-SQL users
Included
Visual Explorer works on a SQL result
Built-in customer embed portal
Included
White-label embeds, no tenant portal
Native Alert with auto-escalation
Included
Report alerts, no escalation policy
Native scheduled subscription (4 providers)
Included
Scheduled report email only
Visual query builder and raw SQL, round-trip convertible
SQL ⇄ visual
SQL and notebooks, no visual spec
Azure AD + Google + LDAP + Basic simultaneously
Included
SAML SSO Enterprise, no LDAP
OIDC SSO user provisioning
Included
Enterprise tier only
AI with on-prem option (Ollama, LM Studio)
Included
Cloud AI only
Multi-tenant architecture out of the box
Included
Single organization per workspace
Connects to your existing warehouse on day 1
40 connectors
Warehouse connections
Flat pricing (unlimited users)
Included
Per-seat, annual blocks
Productive in under 5 minutes
Included
Fast for SQL users, less so for others
EU data residency (native, not a tier)
Included
Enterprise region pinning
No marketplace plugin required for basics
Included
Integrations catalogue
Dashboards and shared reporting
Included
Included
REST API + webhooks
Included
Included
OLAP models with rollup and period-over-period
Included
Reusable queries, not OLAP models
Markdown analysis reports with export
Analysis reports
Markdown cells in notebooks
Legend Included Partial / extra cost Not available
01 / Governance

A notebook is not a governed BI layer

Mode gives an analyst a SQL editor, a Python or R notebook and a report builder in one document. What it does not give the organisation is the layer underneath: a verified badge with an audit log, results materialised on a refresh interval, a per-user query budget and a governor, or a modelled star schema whose filters are always applied as a security boundary. The moment somebody asks "which of these four reports is the one finance signs off?" the limits show.

Qrly is built as a BI platform first. Verification with an audit log, result materialisation, four opt-in caching tiers, the query governor and OLAP models with rollup, cube and grouping sets are part of the core, not a convention the team agrees to follow. Permissions run Tenant to Organisation to Project to Collection, so analysts, engineering and finance each get their own surface without a second installation.

02 / Pricing

The meter is people

Mode does not publish a price for its paid plans — they are quoted, per user, on an annual commitment — so the sticker is whatever comes back from a sales cycle. What is public is the shape of it, and the shape is what matters: the bill tracks headcount, and OIDC, SAML and region pinning sit in the top tier. The question to take into the renewal is not what the number is today, but what happens to it the year those reports become something the whole company reads.

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. That is €18,900 over three years for one organization, not the first-year run rate of a per-seat tool. Headcount growth, new teams, external contractors and the occasional customer-facing portal user do not change the bill. Annual fee on revenue, unlimited everything, one organization, one installation, and you move on.

03 / Self-host

No self-host option

Mode is SaaS only. Data residency is tied to the Enterprise upsell, there is no on-prem option, and no path for regulated or air-gapped teams. For defence, healthcare, finance, and public-sector teams this is usually a non-starter — procurement simply cannot approve a tool that cannot run inside the organisation's own network perimeter.

Qrly runs on your Linux box, your Kubernetes cluster, or your sovereign-cloud tenant. No data leaves your boundary if you do not want it to. Backups, encryption keys, audit logs and user directories stay inside the same controls you already apply to the rest of your stack. If your security team maintains a "no external SaaS for sensitive data" policy, Qrly fits that posture without exceptions.

04 / Tiers

Enterprise features live behind tiers

SSO, OIDC, audit log, data residency and the admin console live on Enterprise or Enterprise+. The features you need to deploy Mode responsibly at 50+ users are rarely in the tier you first signed up on, and the upgrade path involves a sales conversation rather than a self-serve toggle. Teams that adopt Mode bottom-up often hit this wall twelve months in.

Qrly ships SSO, OIDC, audit log and EU data residency in every license. Compliance is a default, not an upgrade path. Administrators do not have to justify a tier jump to IT security to enable the controls IT security already requires — the controls are already there on day one.

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.

Mode

Per user, annual · paid plans quoted · now part of ThoughtSpot
  • How it charges Per user, on an annual commitment
  • Free tier Small teams, limited
  • Paid plans Quoted — contact sales, see mode.com/pricing
  • Deployment Mode cloud only — no self-hosted edition
  • Enterprise controls SSO and region pinning sit in the top tier
  • Ownership Mode has been part of ThoughtSpot since 2023
Mode’s paid plans are quoted rather than listed, so there is no defensible three-year figure to put here. What is knowable before a call: the meter is people, SSO and data residency live in the top tier, and the roadmap now sits inside ThoughtSpot. Qrly ships SSO and EU residency at the €900 floor.

The standard migration path

Everything worth taking out of Mode is SQL. Mode's API exposes the query behind every report, and the report editor shows it too, so most teams script a one-shot export and keep Mode read-only during a short overlap. The real work is deciding which reports deserve to become governed questions.

  1. Export the queries. Pull the SQL behind every report using a personal access token or a service account, and keep the report title, owner and last-run date alongside it. That inventory is what tells you which fifteen of your two hundred reports anyone actually opens.
  2. Recreate the connections. Point Qrly at the same warehouse. Qrly speaks 40 connection types and compiles to 12 SQL dialects, and every connection is handed out as a read-only pooled user with a per-statement timeout, a max-row cap and a concurrency limit.
  3. Paste the SQL in. Mode parameters become Qrly template variables, bound as prepared-statement parameters rather than substituted into the string. The sanitizer accepts SELECT and WITH only, so anything that was quietly writing to the warehouse surfaces on the first run instead of the first incident.
  4. Convert what is worth converting. Any flat SELECT reverse-engineers into a visual QQL definition — joins, filters, group by, having, order by with NULL ordering, limit and offset — which is what unlocks drill-down, interactive filters and dialect portability. CTEs, UNION and subqueries are flagged as lossy and stay as native SQL.
  5. Sync users and run in parallel. Point Qrly's OIDC endpoint at Azure AD, Okta or Google so people keep their existing credentials, then keep Mode read-only for 30 days. Analysts who want a notebook for exploratory work can keep one — Qrly does not need to be an all-or-nothing replacement.
Is Qrly a Mode alternative for analytics teams?

It depends on the work. For an analyst who lives in a SQL-and-Python notebook and publishes an ad-hoc report at the end of it, Mode is genuinely excellent and Qrly is not trying to replace that. For teams that need governed, reusable questions — verified badges, materialised results, alerts, dashboards, embedded analytics and self-hosting — Qrly is the better fit. Many teams run both side by side — Mode for exploratory notebook work, Qrly for the questions the business reads every morning — and that is a perfectly reasonable end state. The switch becomes urgent when a notebook output has quietly become the reporting layer and nobody can tell which version is current.

Can Qrly import Mode reports?

Everything worth moving is SQL. A Mode report is built on a query, and the query text comes out through Mode's API or straight from the report editor. Point Qrly at the same warehouse, paste the SQL into the native editor, and Qrly reverse-engineers any flat SELECT into a visual QQL definition — joins, filters, group by, having, order by with NULL ordering, limit and offset. CTEs, UNION and subqueries are reported as lossy and stay as native SQL. Mode parameters become Qrly template variables, bound as prepared-statement parameters rather than substituted into the string, so the query you paste is the query that runs.

What about Mode's Python and R notebooks?

Qrly has no notebook. There is no Python or R cell and no place to run pandas next to a query — if that is the centre of your workflow, keep Mode. What Qrly gives you instead is the governed layer beneath the analysis: OLAP models with rollup, cube and grouping sets, period-over-period comparison, calculated fields, verified questions with an audit log, and an AI layer running on a local or cloud LLM of your choosing. In practice the split is clean: exploratory statistical work stays in a notebook, and the numbers the business reads every week become Qrly questions.

Why pick a dedicated BI platform over Mode?

Because a reporting layer needs things a notebook product is not built for: verified questions with an audit log, result materialisation on a refresh interval, alerts with multi-channel fan-out, cross-dialect QQL operators (regex, JSON, range, full-text search), a customer-facing analytics portal behind signed JWT, scheduled subscription pipelines across multiple mailboxes, and self-hosting. These are first-class in Qrly. The symptom is usually the same one: nobody can say which of four similar reports is the one finance signs off, so the real reporting layer quietly becomes a spreadsheet somebody re-pastes every Monday.

Does Qrly have a visual builder for people who do not write SQL?

Yes. QQL is a visual query builder first — pick a source table, add filters from around 35 operators, group, aggregate, join and order without typing SQL, and the compiler emits the right dialect for whichever of the 40 connection types you are on. The generated SQL is always readable, and a flat SELECT converts back into the builder, so SQL and point-and-click are two views of the same question rather than two separate tools. Analysts keep the Monaco editor with schema-aware autocomplete, EXPLAIN and AI explain; everyone else never has to open it.

How much is Qrly for 50 users over 3 years?

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. Mode’s paid plans are quoted rather than listed, so there is no defensible figure to put beside that, and we would rather leave the column empty than fill it with a guess. What is public is the model: per user, on an annual commitment, with SSO and region pinning in the top tier. On Qrly the 80th or 150th user costs nothing; on any per-seat tool that same growth compounds into the renewal.

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