SQL Query Analyzer

SQL Query Analyzer is a lightweight and efficient desktop utility designed to simplify the process of managing SQLite, PostgreSQL, SQL Server and MySQL/MariaDB databases.

It is a fork of SQLite Query Analyzer that talks to database servers as well as SQLite files.

It provides an intuitive interface for executing queries and direct table editing, making database operations seamless and straightforward.

• Cross platform - Runs natively on Windows, MacOS, and Linux
• Works with SQLite files and PostgreSQL, SQL Server and MySQL/MariaDB servers
• Connect dialog with a Test Connection button; recent connections are remembered (passwords never are)
• Schema-aware database tree showing schema.table for providers that have schemas
• Easy-to-use interface for executing SQL queries
• Fast table data editing
• Persists application state and reloads last session on startup
• Export database schema as CREATE TABLE statements
• Export data as an SQL script containing INSERT statements or as CSV files
• Zoom the query editor and database tree independently, each with its own size, using Ctrl +/- on the focused pane or Ctrl + mouse wheel over it. The query result grid, Messages pane and Table Data grid zoom together with the query editor, and answer both gestures themselves
• Desktop color theme awareness with automatic switching between dark/light themes
• Command line interface for automation and scripting

The official Qt binaries for Windows and macOS do not include the QMYSQL driver, so MySQL/MariaDB support there needs a Qt build that has it.

Use File > Connect... (Ctrl+Shift+O) to open any provider. File > Open and File > New still open and create SQLite files directly.

The command line, the recent connections list and the saved session all describe a connection in a single line:

SQL Server takes these extra query options: trust=1 accepts a self-signed server certificate, integrated=1 uses Windows authentication, and driver=... names another ODBC driver. A password is never written out. On the command line, give it with --password, the SQLQUERY_PASSWORD environment variable, or inside the URL (postgres://user:secret@host/db).

• Scripts are split into statements on ;, so PostgreSQL $$ function bodies and a ; inside a string literal are not understood yet.
• A SQL Server script that uses GO runs one batch at a time, like sqlcmd: a line holding only GO ends a batch, and GO 5 runs it five times. A batch goes to the server whole, so a procedure body keeps its semicolons, but a batch holding several SELECTs shows only the first result. A script without GO is split on ;.
• The table data grid for PostgreSQL and SQL Server reads the whole result set on the client, so paging only happens in the view.
• Views, stored procedures and other databases on the same server are not listed in the tree.
• Shrink runs VACUUM on SQLite and PostgreSQL and DBCC SHRINKDATABASE on SQL Server. It is disabled for MySQL.

Invoke-RestMethod https://christianhelle.com/sqlquery/install.ps1 | Invoke-Expression

curl -fsSL https://christianhelle.com/sqlquery/install.sh | bash

Pre-built binaries for all platforms are available on the GitHub Releases page.

For more detailed installation instructions, visit the Documentation Website.

SQL Query Analyzer can be used as a command line tool for automating database operations without the GUI. The application supports several command line options for exporting data, executing SQL scripts, and more.

$ sqlquery --help
Usage: sqlquery [options] database
A fast and lightweight cross-platform command line and GUI tool for querying and manipulating SQLite, PostgreSQL, SQL Server and MySQL databases

Options:
  -h, --help                          Displays help on commandline options.
  --help-all                          Displays help, including generic Qt
                                      options.
  -v, --version                       Displays version information.
  -p, --progress                      Show progress during copy
  -e, --export-csv                    Export data to CSV.
  -d, --target-directory <directory>  Target directory for export.
  -r, --run-sql <file>                Execute SQL file.
  --password <password>               Password for a server connection.
                                      Defaults to the SQLQUERY_PASSWORD
                                      environment variable.

Arguments:
  database                            SQLite file or connection URL to open,
                                      e.g. postgres://user@host:5432/db,
                                      mysql://user@host/db or
                                      mssql://user@host/db?trust=1

sqlquery /path/to/database.db

# A server connection opens the Connect dialog to ask for the password,
# unless one is given
SQLQUERY_PASSWORD=secret sqlquery postgres://postgres@localhost/shop

# Export every table of a PostgreSQL database to CSV
sqlquery --export-csv -d ./out --password secret postgres://postgres@localhost:5432/shop

# Run a script against SQL Server
SQLQUERY_PASSWORD=secret sqlquery --run-sql seed.sql "mssql://sa@localhost/master?trust=1"

# Export all tables to CSV files in the current directory
sqlquery --export-csv /path/to/database.db

# Export with progress indicator
sqlquery --export-csv --progress /path/to/database.db

# Export to a specific directory
sqlquery --export-csv --target-directory /path/to/export/folder /path/to/database.db

# Execute a SQL script file against a database
sqlquery --run-sql /path/to/script.sql /path/to/database.db

• Export to CSV: Export all database tables to individual CSV files
• Execute SQL Scripts: Run SQL scripts from files against a database
• Progress Reporting: Show progress indicators for long-running operations
• Flexible Output: Specify custom directories for exported files

Here are some screenshots of SQL Query Analyzer in action:

• Git 😄
• CMake 3.16 or later - Install from official website
• Qt 6.4.2 or later, 6.11.2 recommended - Install from official website
• Powershell Core (Optional)

git clone https://github.com/christianhelle/sqlquery.git
cd sqlquery

Use the Makefile on Linux and macOS, or the cross-platform PowerShell script on Windows:

# Linux / macOS
make

# Windows
pwsh build.ps1

The build output folder is under build on all platforms. On Linux, make also installs into ./linux/.

Install CMAke and Qt6 and XKB

sudo apt-get update
sudo apt-get install -y cmake qt6-base-dev libxkbcommon-dev

Build project

make

Install the Qt SQL drivers for the servers you want to reach (Ubuntu package names)

sudo apt-get install -y libqt6sql6-psql libqt6sql6-mysql libqt6sql6-odbc

Create installable packages (DEB, RPM, 7Z, ZIP, and compressed archives)

make package

Install a sqlquery symlink to ~/.local/bin

make install

Install CMake and Qt6. It's recommended to install Qt using the official installer

brew update
brew install cmake
brew install qt@6

Build project

make

Build MacOS disk image (Optional).

There is a bug in the Homebrew distribution of Qt which causes the use of macdeployqt to fail.

make package

Build the project (These instructions assumes that Qt root folder is C:\Qt)

cd src
cmake . -DCMAKE_PREFIX_PATH=C:/Qt/6.11.2/msvc2022_64 -DCMAKE_CXX_STANDARD=17 -DCMAKE_CXX_FLAGS="/Zc:__cplusplus /permissive-" -B build
cmake --build build --config Release
C:\Qt\6.11.2\msvc2022_64\bin\windeployqt.exe .\build\Release\SQLQueryAnalyzer.exe

Build the installer project using Inno Setup (Optional)

../deps/innosetup/ISCC.exe dist/setup.iss

The unit tests use in-memory and temporary SQLite databases and need nothing else:

make test

The provider integration tests in tests/test_providers.cpp run against real servers. A provider is skipped unless its connection URL is set:

docker compose -f tests/docker-compose.yml up -d
export SQLQUERY_TEST_PG='postgres://postgres:SqlQuery_2026@localhost:5432/postgres'
export SQLQUERY_TEST_MYSQL='mysql://root:SqlQuery_2026@127.0.0.1:3306/test'
export SQLQUERY_TEST_MSSQL='mssql://sa:SqlQuery_2026@localhost:1433/master?trust=1'
./build/tests/SQLQueryTests --gtest_filter='Servers/*'

The Tests GitHub workflow runs both against PostgreSQL, MariaDB and SQL Server service containers.

We welcome contributions to SQL Query Analyzer! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request on GitHub.