Can I connect InfluxDB time-series data to iDBQuery?
Not as a native time-series client — but you can analyse InfluxDB data with iDBQuery by exporting measurements to CSV or reading them through its API. iDBQuery then queries that data in plain language with cited answers. If you use TimescaleDB, iDBQuery connects to it directly as Postgres.
iDBQuery natively connects to SQL databases, spreadsheets, files, documents, REST APIs, and SQL data warehouses. InfluxDB is a purpose-built time-series database with its own query languages (InfluxQL/Flux), so it isn't a native connection — but its data is easy to bring into iDBQuery.
Options:
- Export to CSV — InfluxDB can export measurements to CSV over its API or CLI. Point iDBQuery at those files and query them in plain language.
- Read through its API — connect iDBQuery to InfluxDB's HTTP API as a REST source and treat the results as a dataset.
Once loaded, iDBQuery writes the SQL, returns charts and tables, and cites every figure. Time-series questions like 'average sensor reading per hour last week' or 'peak load by day' work naturally, and you can blend the metrics with relational context — joining device readings with an asset table in Postgres, for example — in one live model.
Worth noting: if you're choosing a time-series store or already run TimescaleDB, that's built on PostgreSQL, so iDBQuery connects to it directly through its Postgres connector with no export step. Many teams standardise on Timescale precisely so their time-series data is queryable by any SQL tool, iDBQuery included.
Updated 2026-06-22