How does iDBQuery join data across different sources?

iDBQuery joins across sources by first building one live queryable model over everything you have connected: a MySQL database, a Postgres warehouse, an Excel sheet, a Google Sheet, a REST API, even a folder of PDFs. Once connected, they behave like tables in a single system.

When you ask a question that spans them, iDBQuery: - Uses the semantic layer to understand each source's schema, including cryptic column names. - Writes cross-source SQL and runs it through its federation engine. - Returns the answer with every figure cited back to the specific source it came from.

A worked example: 'Join signups from our product database to revenue in the billing export and support tickets from the CSV, then show revenue and ticket count per customer.' iDBQuery resolves the keys across the three sources and returns one cited table.

The differentiator is that there is no ETL, no pipeline, and no warehouse project to build first; the join happens at query time against live data. Compare that to a traditional stack, where combining three systems means modelling them into a warehouse before you can ask anything. iDBQuery queries in place, so you can answer a cross-source question the moment the sources are connected, and trace each number back to its origin row.