What is data federation?
Data federation is querying multiple separate data sources in place and combining the results as if they were one database, without first copying everything into a central store. iDBQuery uses federation to answer one question across your databases, spreadsheets, documents and APIs at once.
Traditionally, to analyse data from several systems together you have to consolidate it: extract from each source, transform it, and load it into a single warehouse. Data federation takes the opposite approach — it leaves the data where it lives and queries each source on demand, then merges the results into a single answer.
iDBQuery applies federation so that a single plain-language question can reach into a production database, an uploaded spreadsheet, a folder of PDFs and a REST API simultaneously, and return one coherent result.
Federation gives you:
- No central copy to build or maintain — your data stays in its systems of record.
- Cross-source answers immediately — connect sources once, then ask questions that span all of them.
- Up-to-date results — each query hits the live source rather than a periodic export.
The trade-off federation usually carries is complexity — joining different systems sensibly is hard. iDBQuery handles that by introspecting each source's schema, applying a semantic layer so it understands what fields mean, and writing the queries for you. You get the breadth of a warehouse-style analysis without the cost and delay of building and feeding a warehouse.
Updated 2026-06-22