Sigma is a spreadsheet-shaped cloud BI with AI features locked behind a separate Sigma AI Pro subscription and no on-prem AI option. Qrly is BI + AI in one self-hostable platform — natural-language Ask (NL→SQL), anomaly detection and schema descriptions all running on your choice of local LLM (Ollama, LM Studio) or cloud (Anthropic Claude, Google Gemini, OpenAI, Azure OpenAI), with flat pricing for unlimited users.
No marketing fluff. Sigma is a well-regarded product with a long track record — here is where each tool is genuinely stronger, and where teams consistently land during evaluation calls.
The features most teams actually evaluate when comparing Qrly and Sigma.
From real migration conversations with engineering and support leaders.
Sigma's HelpDesk product does add a customer portal, agent roles and Alert timers — but it is a separate role type that often requires upgraded packs, and its self-service surface is lighter than dedicated tools. The tracker side and the embedded analytics side are governed by different seat accounting, different permission scopes and, in practice, different onboarding paths for your users.
Qrly's embedded analytics is the same surface as the tracker. One permission model, one data model, one upgrade path. External customers file questions through a portal that is just another project view, internal engineers triage those questions alongside their regular issues, and the audit trail is continuous from customer report to code fix.
Sigma InCloud and the Server packs scale gracefully through mid-size: the 50-user bill is reasonable, the 150-user bill is still fine. Above 500 users the per-user price drops slowly and HelpDesk agents are charged on top of tracker seats, so the total bill drifts upward — and the contract gains renewal mechanics, pack arithmetic and agent-vs-user seat distinctions that procurement has to model every year.
Qrly's flat license never scales with headcount. The 51st user costs nothing. Neither does the 501st. Budget conversations become a one-line item, forecasting is trivial, and there is no structural pressure to argue about who really counts as a seat.
Sigma's AI features route through JetBrains AI — a paid subscription that ships prompts to JetBrains-hosted and third-party cloud LLMs. The quality is good, but for regulated teams, legal, finance or public-sector operators the data-flow shape is often a non-starter regardless of feature depth, because the prompts still leave the perimeter.
Qrly ships AI with a local option: point it at an Ollama or LM Studio endpoint on your own hardware and every prompt, every question body and every attachment summary stays inside your network. No JetBrains AI subscription, no third-party data-sharing clause, no renegotiation when a sensitive project starts.
Sigma is a great product, but inside JetBrains it competes for attention with IntelliJ, Rider, Qodana, Toolbox, AI and a growing portfolio of developer tooling. Product priorities follow that portfolio, which is rational for JetBrains but leaves the tracker subject to decisions made about neighbouring SKUs.
Qrly is a dedicated, focused product. Its only job is business intelligence and support. Every release goes into that one surface — no split engineering, no IDE vendor lifecycle dictating when the tracker gets attention, and no risk that the embedded analytics becomes a second-tier feature in someone else's product strategy.
List prices as of 2026-04. 50-user team, 3-year total cost of ownership.
Most teams are up and running on Qrly within a working week.
Qrly reads Sigma via its mature REST API — no third-party ETL required, no brittle CSV dance, and no waiting on a JetBrains support question to unlock an export. Teams with mid-size Sigma instances typically finish the cutover in under a week, and larger enterprises run a parallel window of thirty days before decommissioning the old instance.
For most teams — yes. Sigma and Qrly share the same tracker philosophy: projects, issues, powerful queries, customisable workflows, strong Git-provider integration and a developer-first editing experience. Qrly adds a built-in customer embed portal as the same surface as the tracker, flat pricing for unlimited users, on-prem AI via Ollama or LM Studio, a multi-tenant architecture, and OIDC as a standard feature rather than an enterprise upsell. If your whole team lives inside IntelliJ all day, Sigma's IDE integration will be missed — for everyone else the fit is close, and the contract shape is simpler.
Yes. Qrly reads Sigma exports via the Sigma REST API and maps projects, issues, comments, attachments, custom fields, users and full issue history so QQL WAS / CHANGED queries keep working on migrated data.
Sigma's plugins for IntelliJ, PyCharm, Rider and the other JetBrains IDEs are genuinely excellent if your whole team lives there. Qrly integrates via REST API and Git webhooks, which covers the core workflows (branch linking, PR references, commit-to-issue) from any IDE — VS Code, Neovim, the JetBrains family — without coupling the tracker to one vendor's product line.
Qrly includes in-question rich documentation and project-level pages, which covers the everyday overlap with Sigma Knowledge Base. Teams that need a full wiki often pair Qrly with BookStack, Outline or Notion for dedicated docs — the same separation of concerns that many Sigma customers land on anyway.
Sigma's query language is one of the best in the market — concise, flexible and familiar to power users. QQL offers the same logical richness plus explicit historical operators (WAS, CHANGED, BEFORE, AFTER) so you can query issue state over time without exporting to a report.
€1,875 per year per tenant on the cheapest tier (The Pulse), with unlimited users & projects inside the tenant — €5,625 over three years for a single tenant. Sigma InCloud for 50 users runs roughly €7,900 over three years (list prices as of 2026-04) before HelpDesk agent seats and JetBrains AI Pro, which are billed separately. On-prem Sigma Server packs can be competitive at small scale but the per-user price drops slowly once you grow past a few hundred users.
Self-hostable. Flat pricing. Built-in embedded analytics. On-prem AI. Made in Belgium.