Which File Formats Can TextQuery Import?

TextQuery imports three families of files: data files (.xlsx, .xls, .csv, .tsv), structured data (.json, .jsonld), and compressed archives (.zip, .gz, .tgz, .tar). You don't need to define a schema, write code, or run commands first — the app turns the file into a table on import. If your file is in one of those formats, it should open directly; if it isn't, you'd need to convert it first.

Supported formats at a glance

What "no schema needed" actually means

Normally, loading a raw file into a database means declaring column names and types before anything can be queried. TextQuery skips that step: you point it at a file, and it infers the table structure so the data is queryable with SQL right away. That's the practical difference for the formats above — a .csv or .xlsx becomes a table you can query without a setup script.

Choosing what to import

• Already have a spreadsheet? Use .xlsx or .xls.
• Exporting from another tool? .csv and .tsv are the most portable and usually the safest choice.
• Working with API or web data? .json and .jsonld fit naturally.
• Received a bundle of files? .zip, .gz, .tgz, and .tar can be imported as archives.

Common snags

• Format not on the list. If your file is something else (for example, a proprietary binary format or a database dump), convert it to CSV or JSON first.
• Archives with mixed contents. A .zip or .tar may hold several files; expect to deal with each file's own format once extracted.
• Delimiter confusion in .csv/.tsv. If columns look wrong after import, the delimiter or quoting is the usual culprit.

Verifying the import worked

After importing, check that the row count and column names match your source file, then run a simple SELECT against the table. If the numbers line up, the inferred schema is sound and you can move on to querying or charting.

TextQuery is a desktop app for macOS and Windows, and a free version is available to evaluate before upgrading.