iDBQuery vs Sigma Computing: what's the difference?

Sigma is warehouse-native. It puts a familiar spreadsheet-like grid on top of a cloud data warehouse and live-queries it, so business users can explore governed warehouse data with formulas they already understand. If your data is consolidated in a cloud warehouse and you like a spreadsheet metaphor, Sigma is a great fit.

iDBQuery differs in two important ways:

• No warehouse prerequisite. iDBQuery connects to warehouses too, but it does not require one. It unifies relational databases, spreadsheets, Google Sheets, PDFs, folders of files (with OCR) and REST APIs, plus warehouses, into a single live model.
• Ask, do not build. Instead of composing spreadsheet workbooks, you type a plain-language question; iDBQuery writes the SQL, runs it, and returns a cited number, chart or dashboard.

On top of that, every figure iDBQuery returns links to the exact source rows, and it can deploy in the cloud, your VPC, a Desktop app, or fully air-gapped, so data never has to move to a warehouse or a vendor cloud to be analysed.

Choose Sigma when your data already lives in a cloud warehouse and you want spreadsheet-style exploration. Choose iDBQuery when your data is spread across many systems and files, or when you need cited answers and flexible, in-your-walls deployment.