iDBQuery vs Defog (SQLCoder) text-to-SQL: how do they compare?
Defog centres on text-to-SQL models and APIs (such as the open-source SQLCoder) that developers integrate to translate questions into SQL, whereas iDBQuery is a complete product that runs the query, cites every figure to its source row, joins multiple sources, and deploys in the cloud, your VPC or air-gapped.
Defog is known for text-to-SQL technology — including open-source SQLCoder models and APIs — that turns a natural-language question into a SQL query for developers to run inside their own applications. It's a building block. iDBQuery is the end-to-end product around that idea.
- From question to answer, not just to SQL. iDBQuery writes the SQL, runs it against your live model, and returns a number, chart, table, live dashboard or shareable report — you don't wire up execution yourself.
- Cited results. Each figure links back to the exact row behind it, so answers are auditable.
- Cross-source model. It joins databases, spreadsheets, PDFs and APIs into one live model, rather than generating SQL for a single pre-defined schema.
- Semantic understanding. A semantic layer helps it handle cryptic schemas without you hand-tuning prompts and context.
- Deployment and governance. Cloud, VPC, air-gapped, Desktop or Embedded SDK, with read-only querying and access controls included.
Defog-style models and APIs are ideal if you're an engineering team embedding text-to-SQL into your own software and want control over the generation step. iDBQuery is the better choice when you want a finished, cited, cross-source answering experience for a team without building and operating the surrounding system.
Updated 2026-06-22