iDBQuery vs Qlik Sense: what's the difference?
Qlik Sense is a powerful data-exploration tool built on an associative in-memory engine, great for interactive dashboards once data is loaded into its model; iDBQuery skips the load step, querying your sources in place, answering plain-language questions, and citing every figure to its source row.
Qlik Sense is known for its associative engine: load data in and users can explore freely, following relationships across fields. For teams that want rich, interactive self-service dashboards and are happy to build and refresh a Qlik data model, it is a mature choice, available in cloud or on-premises.
Where iDBQuery differs:
- Query in place, no load script. iDBQuery does not ingest your data into an in-memory model; it builds one live queryable model and runs SQL against your sources directly, so there is no reload cycle to manage.
- Conversation over exploration. Rather than clicking through selections, you ask a question in plain language and get a direct, cited answer, with a chart or dashboard when it helps.
- Auditable numbers. Every figure cites the exact source rows, which matters when a result feeds a board pack or a regulator.
- All your sources, including files. Databases, warehouses, Excel, CSV, Sheets, PDFs, folders with OCR and REST APIs come together in one model.
Qlik Sense rewards teams who invest in its associative model and enjoy visual exploration. iDBQuery is aimed at people who just want to ask a question, trust the cited answer, and not maintain a data-loading pipeline to get it.
Qlik Sense and iDBQuery, side by side
| Qlik Sense | iDBQuery | |
|---|---|---|
| How you explore | Associative model — click to filter and follow relationships | Ask the question in words |
| Before you start | Load script, data model, app design | Connect a source |
| Skill required | Qlik scripting and app authoring | None beyond stating the question |
| Unstructured sources | Needs extraction upstream | PDFs and documents queried alongside tables |
| Provenance of a figure | The app shows the number | Every number links to its source row and query |
| Deep interactive exploration by a power user | Where the associative engine shines | Answers a question, then lets you take the SQL |
When the other one is the right choice
Choose Qlik when the associative exploration model fits how your analysts think — following relationships by clicking, and noticing what is *not* selected, is genuinely distinctive and some teams are extremely productive in it. That strength assumes someone has built the app. iDBQuery is for the question that arrives before anyone has built anything.
Updated 2026-08-08