
Analysis Services Scripting Language (ASSL).Transact-Structured Query Language (T-SQL).How about language support? In SMSS, you can write in Microsoft-specific data access and analysis languages: With regard to the user interface, Azure Data Studio has a more modern and streamlined user interface, while SSMS has a more traditional interface that may be more familiar to experienced SQL Server professionals. Working in a Jupyter notebook in Azure Data Studio Jupyter notebooks provide a nice way to combine Markdown-formatted documentation with live code that you can execute directly within the notebook.
#Azure data studio plugins software#
The Git integration is particularly notable in today's DevOps-central software development landscape.
#Azure data studio plugins update#
Maintenance: Tools for managing database maintenance tasks, such as index defragmentation and statistics update.Security: Tools for managing users, roles, and permissions, and for implementing security policies.Backup and Restore: Create database backups and restore them in the event of data loss.


Note that you can use SSMS to connect to Azure SQL Database and Azure Synapse SQL pools, as well as local SQL Server databases. For example, being able to work in the Cosmos DB outside the Azure portal would be useful.īy contrast, SSMS is a more fully featured tool that is intended for DBAs and other IT professionals who need to manage and configure SQL Server instances. Personally, I was disappointed that Microsoft chose not to embrace NoSQL databases in Azure Data Studio. Open source software like Azure Data Studio symbolizes the new Microsoft Target audienceĪzure Data Studio is focused on providing a streamlined experience for data professionals and developers working with SQL Server, Azure SQL Database, and Azure Synapse SQL pools.
