# multiprocessio/dsq

Commandline tool for running SQL queries against JSON, CSV, Excel, Parquet, and more.

Repository: https://github.com/multiprocessio/dsq
Canonical: https://ross.abutalabs.com/products/dsq
Language: Go
License: NOASSERTION
License Family: other
Topics: golang, csv, json, tsv, excel, openoffice-calc, parquet, sql, cli
Last push: 2023-09-30T14:49:59+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 1696, "days_push": 1068, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3866, forks 162 (observed 2026-08-28T04:08:27.666187+00:00)

## What it is
dsq is a Go command-line tool that lets you run SQL queries directly against data files such as JSON, CSV, TSV, Excel, and Parquet, powered by SQLite under the hood. It is a CLI companion to the DataStation GUI and supports piping, joins across files, and schema introspection.

## Use cases
- run sql queries against a csv file from the command line
- query json files with sql
- join multiple csv and json files with sql
- convert excel or parquet data to json
- inspect the inferred schema of a data file
- ad-hoc analytics on local data files without loading a database

## When to avoid
- you need high-performance analytics on large datasets - the project recommends DuckDB, clickhouse-local, or GlareDB instead
- you need actively developed software - the project is not under active development
- you need column-oriented storage, vectorized execution, or advanced SQL features beyond SQLite

## Facets
- artifact type: cli-tool
- maturity: maintenance
- function: cli, database, etl, data-science, parser
- domain: data-science, developer-tools, files, analytics
- platform: cli, cross-platform, windows, go
- tags: sql-queries, data-files, sqlite, json, csv, parquet, excel, data-wrangling, command-line, macos, linux

## Member repositories
- multiprocessio/dsq (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:27.666187+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:25:51.080280+00:00, confidence not recorded.
  - readme: https://github.com/multiprocessio/dsq (fetched 2026-08-28T04:08:27.666187+00:00, sha c20c75601626)
- Data as of 2026-08-30T08:39:29.467469+00:00.