Azure Data Studio is a free cross-platform database client for SQL Server and Azure SQL that combines a T-SQL editor with notebooks, chartable result grids, an integrated terminal and extension support.
Azure Data Studio is a lightweight database client Microsoft built for people who spend their day writing and running queries. It opens to a connections panel instead of a wizard, and a query editor with IntelliSense, snippets and Git integration handles the rest of the work. Results come back in a grid that can be exported or charted without leaving the window, and SQL notebooks mix markdown notes with executable cells for repeatable investigations. Because Azure Data Studio runs on Windows, macOS and Linux, the same connection profiles and keyboard habits travel between machines. Microsoft has since retired the tool and points new work at the MSSQL extension for Visual Studio Code.
Day-to-day use is centred on the query editor. Multiple tabs keep several scripts open, smart snippets generate the SQL for creating databases, tables, views, procedures and logins, and on-demand queries run without a separate console. Results can be copied, saved as text, JSON or Excel, or pushed into the chart viewer for a quick look at a metric before anyone builds a report. Connection management is deliberately simple: server groups hold related servers, profiles keep credentials separate, and the object browser exposes databases and tables in a tree. Extensions are where Azure Data Studio grows, adding schema compare, backup and restore, migration helpers, dashboards and Copilot-style assistance without bloating the base editor.
The first benefit is speed of routine work. Opening Azure Data Studio costs far less than a full management suite, and the keyboard-focused editor keeps query writing, execution and result inspection in one window, which matters when the same statement is rewritten a dozen times an hour. The second benefit is cross-platform reach: teams on macOS and Linux get the same tool as Windows users, so database work no longer depends on which laptop was issued. Third, results are immediately useful, because grids export to CSV, JSON or Excel and the chart viewer turns a result set into a picture before a reporting tool is involved. Fourth, SQL notebooks preserve context: the explanation, the query and the output stay in one shareable file instead of a chat message and a screenshot. Finally, the extension model means Azure Data Studio fits different workflows, from schema comparison to migration planning, without installing features nobody uses.
Key capabilities and highlights.
The editor is built for writing statements rather than clicking through dialogs, with IntelliSense, keyword completion, code navigation and reusable snippets for common objects. Azure Data Studio also keeps multiple query tabs and a connection picker in the same window, so context switching between servers costs a click instead of a restart.
Notebooks combine prose, code cells and output in one document, which is how a slow-query investigation gets shared with the query, the finding and the evidence intact. Cells can be run individually against a chosen connection, so a notebook works as both a checklist and living documentation.
Result sets arrive in a grid that can be sorted, copied or saved as CSV, JSON or Excel without another tool. The chart viewer renders the same data as a bar, line or scatter visual in seconds, which is enough for a sanity check on a metric before a report is built in a BI platform.
An integrated terminal runs Bash, PowerShell, sqlcmd, BCP and ssh inside the application, which suits administrators who would rather script a routine than click through it. Azure Data Studio keeps that shell next to the query editor, so a backup command and the query that verifies it live in the same window.
Connection profiles store the details for each server, and server groups keep development, staging and production organised in a tree. Seeing which environment a query tab is attached to reduces the risk of running a statement against the wrong database during a busy release.
The base tool stays small because capability is added through extensions, covering schema compare, backup and restore, SQL Agent, migration assistants, dashboards and AI-assisted coding. Teams install only what matches their workflow, and extension updates arrive independently of the editor itself, which keeps the download light for everyone else.
Schema compare shows the differences between a source and a target database, and the changes can be applied directly or scripted for review. Import and export of DACPAC packages means a schema can be captured as a portable artefact and moved between environments without hand-written migration scripts.
Scripts saved in a workspace can be committed, diffed and branched from inside the editor, which keeps SQL changes in the same review process as application code. Azure Data Studio surfaces the standard source control panel, so no separate client is needed to keep query files under version control.
Browse historical releases and previous builds.
No old versions have been added yet.
Common questions about Azure Data Studio.
It is used to write and run queries, browse database objects, chart results and organise connections, mainly against SQL Server and Azure SQL. Data professionals also use it for SQL notebooks, schema comparison and migration work, because extensions cover those tasks without a heavier management suite.
No. Microsoft has retired Azure Data Studio, so it no longer receives updates, security patches or maintenance. Existing installations keep working, but new projects are directed to the MSSQL extension for Visual Studio Code or to SQL Server Management Studio for deep administration.
Azure Data Studio is lighter and query-first, while SSMS is a full administration console. SSMS covers registered servers, policy-based management, replication, Always Encrypted, live query statistics and database diagrams, which Azure Data Studio either omitted or left to extensions.
SQL Server and Azure SQL are the primary targets. Azure Synapse, MySQL, PostgreSQL and Cosmos DB are reachable through the relevant extensions, which is why the tool was positioned as a cross-platform client rather than a SQL Server-only one.
Yes. It shipped for Windows, macOS and Linux, which is the main reason teams with mixed laptops adopted it. Connection profiles and keyboard shortcuts behave the same across platforms, so a database workflow could move between operating systems without retraining.
They are documents made of markdown text and runnable code cells, saved as .ipynb files and shared like any other project file. Because the notebook support is built on a Jupyter kernel, the same file can also be opened in other notebook environments.
Yes. Results can be copied from the grid, saved as CSV, JSON or Excel, or turned into a chart inside the application. There is no direct results-to-file output like SSMS offers, which is one of the small capability gaps between the two tools.
For query work and light administration, Microsoft points to the MSSQL extension for Visual Studio Code; for deep administration it is SQL Server Management Studio. Notebooks and some migration features have no exact equivalent, so workflows built on them need rethinking.
Azure Data Studio is a free cross-platform database client for SQL Server and Azure SQL that combines a T-SQL editor with notebooks, chartable result grids, an integrated terminal and extension support.
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