# neilotoole/sq

sq data wrangler

Repository: https://github.com/neilotoole/sq
Canonical: https://ross.abutalabs.com/products/sq
Homepage: https://sq.io
Language: Go
License: MIT
License Family: permissive
Topics: sql, golang, go, excel, csv, tsv, json, jsona, jsonl, markdown, xml, xlsx, azure-sql-edge, database, mysql, postgres, sqlserver, data-wrangler
Last push: 2026-08-26T07:18:07+00:00

## Health v2 (maintenance only)
Score: 96/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 90, longevity 100
- inputs: {"age_days": 3852, "days_push": 7, "days_rel": 71, "gap_med": 15, "n_releases_24m": 14}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2555, forks 42 (observed 2026-08-28T04:07:00.717392+00:00)

## What it is
sq is a command-line data wrangling tool that provides jq-style querying over SQL databases and document formats like CSV, Excel, and JSON. It can join across sources, inspect schema metadata, diff tables/databases, and export or insert data in many formats.

## Use cases
- query a postgres table with jq-like syntax from the command line
- join a csv file with a mysql database table
- import an excel worksheet into a postgres table
- export all database tables to csv files
- inspect database schema metadata as  for use with jq
- diff two database tables or entire databases
- convert  lines data into a sqlite table
- run native sql against sql server and insert results into sqlite

## When to choose
- you want jq-style one-liner queries against databases or flat files
- you need to move or convert data between databases and document formats like csv or excel
- you want to inspect, compare, or document database schemas from the terminal
- you prefer a lightweight cli over heavyweight ETL tools

## When to avoid
- you need a full GUI-based data pipeline or orchestration platform
- you need streaming or real-time data processing at scale
- your workflow requires complex transformations better suited to pandas or dbt

## Facets
- artifact type: cli-tool
- maturity: active
- function: database, cli, etl, data-science, csv, pdf
- domain: databases, developer-tools, files
- platform: cli, windows, cross-platform, go
- tags: data-wrangler, sql, jq-style-query, excel, xlsx, cross-source-join, slq, database-diff, data-export, data-import, data-engineering, command-line, macos, linux, docker

## Member repositories
- neilotoole/sq (main) score 96

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:00.717392+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 2026-08-30T02:23:44.073472+00:00, confidence not recorded.
  - readme: https://github.com/neilotoole/sq (fetched 2026-08-28T04:07:00.717392+00:00, sha d460be762ba1)
  - homepage: https://sq.io (fetched 2026-08-29T10:06:30.074947+00:00, sha 62cf0f23f7e2)
  - site_page: https://sq.io/docs/install (fetched 2026-08-29T10:06:30.084146+00:00, sha 67468e5e95b8)
  - site_page: https://sq.io/docs/overview (fetched 2026-08-29T10:06:30.085974+00:00, sha 649ddf35c2ad)
  - site_page: https://sq.io/docs/query (fetched 2026-08-29T10:06:30.087759+00:00, sha 5fabc9fc898a)
  - site_page: https://sq.io/docs/tutorial (fetched 2026-08-29T10:06:30.090583+00:00, sha c26b96a21cd7)
  - site_page: https://sq.io/docs/cookbook (fetched 2026-08-29T10:06:30.092540+00:00, sha 73a103f7aafb)
  - site_page: https://sq.io/docs/diff (fetched 2026-08-29T10:06:30.094164+00:00, sha a88fb26bd72a)
  - site_page: https://sq.io/docs/output (fetched 2026-08-29T10:06:30.095781+00:00, sha f8fdd02695fa)
  - site_page: https://sq.io/docs/inspect (fetched 2026-08-29T10:06:30.097494+00:00, sha 4042cceb7bc6)
- Data as of 2026-08-30T08:39:29.467469+00:00.