iDBQuery vs Wren AI: what's the difference?

Wren AI is an open-source text-to-SQL and GenBI project: you model your data semantically, then ask questions in natural language and it generates SQL and visualisations. It's a capable open framework that you self-host and configure. iDBQuery covers the same natural-language-to-answer goal, delivered as a managed, ready-to-run product.

• Less upfront modelling. iDBQuery introspects your sources and uses a semantic layer to interpret cryptic schemas automatically, so you can ask useful questions before hand-building a full semantic model.
• One model across everything. It unifies databases, spreadsheets, PDFs, folders of files and REST APIs into a single live model — structured and unstructured data together.
• Cited answers. Every number is traceable to its source row for auditing and trust.
• Documents included. OCR ingest makes PDFs and scans queryable alongside your tables — beyond typical SQL-only scope.
• Deployment options. Cloud, VPC, air-gapped, Desktop app or Embedded SDK, with query-in-place.

Wren AI is a strong pick if you want an open-source system and are comfortable maintaining it and defining the semantic model yourself. iDBQuery is the better fit for teams that want cited, cross-source answers — including documents — without hosting and curating the platform.