Why use iDBQuery instead of building a data warehouse?
Building a data warehouse means months of pipelines, ETL and modeling before anyone gets an answer; iDBQuery queries your existing databases, files and APIs in place to give cited answers in minutes — no warehouse, no pipelines. iDBQuery skips the entire ingest project.
A data warehouse is a real investment: design the schema, build pipelines, run ETL, maintain it, and only then start asking questions. For many teams that's overkill, and it still goes stale between loads. iDBQuery removes the prerequisite entirely.
- Query in place. iDBQuery connects to your sources and builds one live model over them — no copying everything into a central store first.
- No pipelines or ETL. There's no ingest project to staff or schedule; you connect and ask.
- Always current. Because it queries the live sources, answers reflect the real state now, not the last warehouse load.
- Spans messy, varied data. Databases, spreadsheets, PDFs and APIs all join into one queryable model.
- Cited and auditable. Every number traces to its source row, so you trust the answer without a governed warehouse behind it.
If you already have a warehouse, iDBQuery connects to it like any other source. If you don't, you may not need to build one just to answer questions. For data residency and scale, iDBQuery also deploys in your own VPC or fully air-gapped, so 'no warehouse' doesn't mean less control.
A warehouse project, or one live model
| Data warehouse | iDBQuery | |
|---|---|---|
| Time to first answer | Months — pipelines, modelling, testing | Same day |
| Ongoing cost | Pipelines and models to maintain as sources change | Sources reconnect; no copy to keep in sync |
| Freshness | As fresh as the last load | Read from the source at query time |
| A second copy of your data | Yes, with the governance that implies | No copy — queried where it lives |
| Very large-scale, repeated analytical workloads | What warehouses are built for | Not a substitute for one |
When the other one is the right choice
Build the warehouse when you are running heavy analytical workloads at scale, when many downstream systems need one governed, conformed version of the truth, or when regulation requires an immutable historical record. Those are real problems and a warehouse solves them properly. iDBQuery is for getting answers now — including while that project is still being built, which is where most teams actually are.
Updated 2026-08-08