Open Source SQL Tool

SQLShell

Query CSV, Parquet, Excel, and more with SQL. DuckDB-powered desktop app — no database setup required.

A fast, local SQL workspace for data analysts and engineers. Open files instantly and run queries without servers, browsers, or cloud dependencies.

File-based querying powered by the DuckDB analytical engine
Keyboard-first: F5/F9 execution, autocomplete, search
Supports CSV, Parquet, Excel, JSON, Delta Lake, SQLite
Runs locally and offline, without external services

Download pip install sqlshell View on GitHub

File Formats

100%

Open Source

Setup Required

DuckDB-based

DuckDB Engine

Built for Data Analysis

Everything you need to explore and analyze data files without the overhead of database servers.

⚡

Analytical Query Performance

Powered by DuckDB's columnar engine, optimized for analytical workloads. Designed for analytical queries over large, columnar datasets.

🎯

Smart Execution

F5 runs all queries, F9 runs just the current statement. Perfect for iterative data exploration and testing.

🧠

Intelligent Autocomplete

Context-aware SQL suggestions that know your tables and columns. Press Ctrl+Space for instant help.

🔍

Instant Search

Ctrl+F to search across all result columns. Find patterns, filter data, and explore results interactively.

📊

Column Profiling

Right-click for instant statistics: data types, null counts, unique values, min/max, and distributions.

🎨

Clean Interface

Distraction-free design with syntax highlighting, result tables, and a familiar SQL editor experience.

Load Any Data Format

Drag and drop files or use the file loader. SQLShell handles the parsing automatically.

📄

CSV

.csv, .tsv

🗂️

Parquet

.parquet

📊

Excel

.xlsx, .xls

📋

JSON

.json

🔺

Delta Lake

.delta

🗃️

SQLite

.db, .sqlite

SQL, The Way You Know It

Write standard SQL queries. Join multiple files. Aggregate, filter, transform.

                    
                    analysis.sql
                

-- Load your CSV and query instantly
SELECT
    category,
    COUNT(*) AS total_orders,
    AVG(amount) AS avg_amount,
    SUM(amount) AS revenue
FROM sales_data
WHERE date >= '2024-01-01'
GROUP BY category
ORDER BY revenue DESC
LIMIT 10;
            

Get Started in Seconds

Download the app or install via pip. Either way, you're ready to query in under a minute.

🪟

Windows

One-click installer. No dependencies needed.

Download .exe

🐧

Linux

Debian/Ubuntu package available.

sudo dpkg -i sqlshell_*.deb

Download .deb

🐍

Python (pip)

Works on any platform with Python 3.8+

pip install sqlshell && sqls

View on PyPI

Keyboard-First Design

Power users love keyboard shortcuts. Here are the ones that matter.

▶️

Run All Queries

⏯️

Run Current Statement

⚡

Quick Execute

Ctrl Enter

🔍

Search Results

Ctrl F

💡

Autocomplete

Ctrl Space