How does iDBQuery handle a query that would return millions of rows?
iDBQuery answers most questions with aggregates — sums, counts, top-N — so it rarely needs to return millions of raw rows. When you do want detail, it summarises and paginates on screen and lets you export the full set to CSV or Excel, keeping the interface fast while still giving you every row.
Business questions usually want a conclusion, not a data dump, and iDBQuery is built around that distinction.
- Aggregate first. "Revenue by month" or "top 20 customers" computes a compact result in the database, so a query over millions of underlying rows returns a small, readable answer plus a chart.
- Detail on demand. When you genuinely need the rows — a full list of overdue invoices — iDBQuery shows a paginated, summarised view rather than freezing the screen with everything at once.
- Full export. For the complete set, export to CSV or Excel and take all the rows into another tool. The heavy result leaves as a file instead of trying to render in the browser.
This keeps the experience responsive while never hiding data from you. It complements querying the full dataset (not a sample) and pushing aggregation to the source: the maths runs where the data lives, and only what you need to see comes back. Every figure and every listed row remains cited to its source, so even a large exported extract stays traceable to where it came from.
Updated 2026-06-22