# explorerhq/sql-explorer

SQL reporting that Just Works. Fast, simple, and confusion-free. Write and share queries in a delightful SQL editor, with AI assistance.

Repository: https://github.com/explorerhq/sql-explorer
Canonical: https://ross.abutalabs.com/products/sql-explorer
Homepage: https://www.sqlexplorer.io
Language: Python
License: NOASSERTION
License Family: other
Topics: sql, analytics, ai, django-application, reporting
Last push: 2025-04-23T01:55:00+00:00

## Health v2 (maintenance only)
Score: 30/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 17, release rhythm 8, longevity 100
- inputs: {"age_days": 4637, "days_push": 498, "days_rel": 708, "gap_med": null, "n_releases_24m": 1}
- 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 2876, forks 372 (observed 2026-08-28T04:07:27.402122+00:00)

## What it is
SQL Explorer is a Django-based SQL reporting and business intelligence application that lets users write, run, and share SQL queries through a web-based editor with autocomplete, pivot tables, and scheduled snapshots. It connects to any Django-supported database as well as uploaded CSV, JSON, or SQLite files, and includes an optional LLM-powered SQL assistant.

## Use cases
- run ad-hoc sql queries against a database from a browser
- share sql query results with teammates via urls
- schedule queries to snapshot changing data over time
- query uploaded csv or  files with sql
- generate pivot tables and charts from query results
- get ai help writing and debugging sql queries
- expose query results as  api endpoints
- email scheduled query reports to stakeholders

## When to choose
- you want a lightweight self-hosted BI tool without heavy setup
- your team already runs Django and wants to embed reporting into an existing site
- you need quick SQL querying, sharing, and scheduled snapshots with minimal configuration
- non-technical users need parameterized queries with a friendly UI

## When to avoid
- you need full-featured enterprise BI with dashboards and drag-and-drop visualization
- you don't want to run a Python/Django application
- you need a no-code analytics tool for non-SQL users end to end

## Facets
- artifact type: application
- maturity: active
- function: database, search-engine, data-visualization, analytics, chatbot
- domain: databases, analytics, data-science, web-development, self-hosted
- platform: python, self-hosted
- tags: sql-editor, reporting, django, business-intelligence, query-sharing, pivot-tables, llm-assistant, web-server, docker

## Member repositories
- explorerhq/sql-explorer (main) score 30

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:27.402122+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 2026-08-30T07:35:42.108624+00:00, confidence not recorded.
  - readme: https://github.com/explorerhq/sql-explorer (fetched 2026-08-28T04:07:27.402122+00:00, sha bc9705afd067)
  - homepage: https://www.sqlexplorer.io (fetched 2026-08-29T09:51:15.495899+00:00, sha 0addf7a5324a)
- Data as of 2026-08-30T08:39:29.467469+00:00.