Why use iDBQuery instead of doing analysis in Excel?

Excel breaks down at scale, across multiple files, and on live data — iDBQuery queries your real databases, spreadsheets, PDFs and APIs together in one live model, answers in plain language, and cites every number. iDBQuery handles the scale and cross-source joins that spreadsheets can't.

Excel is great for small, self-contained analysis, but it strains the moment data gets large, lives in several files, or needs to stay current. Manual VLOOKUPs across workbooks are slow and fragile, and a spreadsheet can't reach into your databases. iDBQuery works where Excel stops.

  • No row limits or copy-paste. It queries source data directly instead of pulling it into a sheet.
  • Joins across everything. Databases, spreadsheets, PDFs and APIs become one live queryable model — no manual lookups between files.
  • Always live. Answers reflect current source data, not a stale export someone downloaded last week.
  • Plain language, not formulas. Ask the question; iDBQuery writes the query.
  • Cited. Every number traces to its source row, so there's no hidden-formula or broken-reference risk.

You can still keep using Excel — connect your spreadsheets as sources, or export iDBQuery results back out. The difference is that iDBQuery treats your spreadsheets as one input among many in a much larger, always-current model, and gives you answers you can audit instead of formulas you have to trust.

Excel and iDBQuery, side by side

ExceliDBQuery
Where the data livesA copy, in a file, as of when it was exportedThe live source
ScaleSlows and breaks past roughly a million rowsQueries the database directly
Joining several systemsVLOOKUP across exports, by handOne model, joined for you
AuditabilityFormulas can drift silently; provenance is lost on exportEvery number traces to its source row
Modelling, what-ifs and one-off shapingUnmatched flexibilityAnswers questions; exports to Excel when you want it

When the other one is the right choice

Excel remains the right tool for building a model, testing a scenario, or shaping something bespoke — the flexibility that makes it hard to audit is exactly what makes it good at that. The case against it is narrower: it is the wrong place to hold the source of truth, and the wrong way to answer a question whose data lives in three systems.

Updated 2026-08-08