DataGripLinux vs Microsoft Azure Data StudioWindows

DataGrip como alternativa Linux a Microsoft Azure Data Studio

Actualizado el 30 de octubre de 2026

Nuestra opinión

DataGrip is a strong, arguably superior, replacement for Microsoft Azure Data Studio for pure SQL development. It offers deeper schema-aware editing, refactoring, and multi-engine support via JDBC. However, it lacks the specific Azure cloud management features and extension ecosystem of Azure Data Studio. If your work is heavy on Azure-specific administration or requires the free, VS Code-based interface, stick with Azure Data Studio. If you prioritize powerful SQL editing, cross-database consistency, and professional-grade tooling, DataGrip is the better choice, provided you are willing to pay for a proprietary license.

Cobertura de funciones85%

Licencia: LicenseRef-proprietary
Precio: paid
Última versión: 2026.2.6 (29 de septiembre de 2026)
Valoración: —

Instalar DataGrip Sitio oficial ↗

Captura de pantalla de DataGrip — Welcome Screen

Lo que funciona igual

Both provide integrated SQL editors with syntax highlighting and autocomplete.
Both support connecting to multiple database engines including SQL Server and PostgreSQL.
Both allow executing queries and viewing results in tabular formats.
Both include tools for managing database objects like tables and views.

Lo que cambia

DataGrip is proprietary and paid, while Azure Data Studio is free and open-source based.
Azure Data Studio has deep integration with Azure cloud services and extensions, which DataGrip lacks.
DataGrip offers more advanced refactoring, schema diffing, and visual diagram tools than Azure Data Studio.
Azure Data Studio uses a VS Code-like interface, while DataGrip uses the JetBrains IDE interface.

Abrir tus archivos de Microsoft Azure Data Studio

DataGrip does not natively open Azure Data Studio workspace files (.code-workspace) or its specific configuration formats. However, since both tools primarily work with standard SQL files (.sql), you can open existing SQL scripts directly in DataGrip. Connection strings and server configurations will need to be manually recreated in DataGrip’s data source settings, as there is no direct import mechanism for Azure Data Studio’s connection profiles.

Pasar de Microsoft Azure Data Studio a DataGrip, paso a paso

Install DataGrip via your package manager or Flathub.
Create new data source connections in DataGrip for your SQL Server and Azure SQL instances.
Import your existing .sql script files into a new DataGrip project.
Reconfigure any automation scripts to use DataGrip’s command-line interface if needed.
Test query execution and result viewing to ensure compatibility with your workflow.

Funciones clave de DataGrip

Conéctate a cualquier base de datos con un controlador JDBC, incluyendo PostgreSQL, Oracle, MySQL y Snowflake
Editor de SQL inteligente con autocompletado consciente del esquema, resaltado de errores y herramientas de refactorización
Múltiples consolas de consulta independientes para ejecutar, explicar y perfiles SQL
Editor de datos tipo Excel con edición en línea, ordenación y exportación a CSV, JSON o Excel
Diagramas visuales de esquema y generación de DDL para objetos de base de datos
Herramientas de diferencia de datos para comparar tablas o resultados de consultas con diferencias visuales
Integración con Git para el control de versiones de scripts SQL y migraciones de base de datos
Asistencia con IA para la generación de SQL a partir de lenguaje natural y explicación de consultas

Cómo instalar DataGrip en Linux

Flatpak (Flathub)flatpak install flathub com.jetbrains.DataGrip

Preguntas frecuentes

Can DataGrip connect to Azure SQL specifically?

Yes, DataGrip connects to Azure SQL via the standard JDBC driver for SQL Server, treating it like any other SQL Server instance.

Is DataGrip free?

No, DataGrip is a proprietary JetBrains product that requires a paid license, unlike the free Azure Data Studio.

Does DataGrip support Azure extensions?

No, DataGrip does not support the VS Code extension marketplace. It relies on its built-in tools and JDBC drivers rather than cloud-specific extensions.