DataGripLinux vs Microsoft Azure Data StudioWindows

DataGrip, alternative Linux à Microsoft Azure Data Studio

Mis à jour le 30 octobre 2026

Notre avis

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.

Couverture fonctionnelle85%

Licence: LicenseRef-proprietary
Prix: paid
Dernière version: 2026.2.6 (29 septembre 2026)
Note: —

Installer DataGrip Site officiel ↗

Capture d’écran de DataGrip — Welcome Screen

Ce qui fonctionne pareil

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.

Ce qui change

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.

Ouvrir vos fichiers 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.

Passer de Microsoft Azure Data Studio à DataGrip, étape par étape

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.

Fonctionnalités clés de DataGrip

Connexion à n'importe quelle base de données avec un pilote JDBC, y compris PostgreSQL, Oracle, MySQL et Snowflake
Éditeur SQL intelligent avec achèvement prenant en compte le schéma, surbrillance des erreurs et outils de refactorisation
Plusieurs consoles de requêtes indépendantes pour exécuter, expliquer et profiler le SQL
Éditeur de données de type Excel avec édition en ligne, tri et export vers CSV, JSON ou Excel
Diagrammes de schéma visuels et génération de DDL pour les objets de base de données
Outils de diff de données pour comparer des tables ou des résultats de requêtes avec des différences visuelles
Intégration Git pour le contrôle de version des scripts SQL et des migrations de base de données
Assistance IA pour la génération de SQL à partir du langage naturel et l'explication de requêtes

Installer DataGrip sous Linux

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

Questions fréquentes

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.