Supported features of Azure SQL Edge

Azure SQL Edge is built on the latest version of the SQL Database Engine. It supports a subset of the features supported in SQL Server 2019 on Linux, in addition to some features that are currently not supported or available in SQL Server 2019 on Linux (or in SQL Server on Windows).

For a complete list of the features supported in SQL Server on Linux, see Editions and supported features of SQL Server 2019 on Linux. For editions and supported features of SQL Server on Windows, see Editions and supported features of SQL Server 2019 (15.x).

Azure SQL Edge editions

Azure SQL Edge is available with two different editions or software plans. These editions have identical feature sets, and only differ in terms of their usage rights and the amount of memory and cores they can access on the host system.

Plan Description
Azure SQL Edge Developer For development only. Each Azure SQL Edge Developer container is limited to up to 4 cores and 32 GB memory.
Azure SQL Edge For production. Each Azure SQL Edge container is limited to up to 8 cores and 64 GB memory.

Operating system

Azure SQL Edge containers are based on Ubuntu 18.04, and as such are only supported to run on Docker hosts running either Ubuntu 18.04 LTS (recommended) or Ubuntu 20.04 LTS. It's possible to run Azure SQL Edge containers on other operating system hosts, for example, it can run on other distributions of Linux or on Windows (using Docker CE or Docker EE), however Microsoft does not recommend that you do this, as this configuration may not be extensively tested.

The recommended configuration for running Azure SQL Edge on Windows is to configure an Ubuntu VM on the Windows host, and then run Azure SQL Edge inside the Linux VM.

The recommended and supported file system for Azure SQL Edge is EXT4 and XFS. If persistent volumes are being used to back the Azure SQL Edge database storage, then the underlying host file system needs to be EXT4 and XFS.

Hardware support

Azure SQL Edge requires a 64-bit processor (either x64 or ARM64), with a minimum of one processor and one GB RAM on the host. While the startup memory footprint of Azure SQL Edge is close to 450MB, the additional memory is needed for other IoT Edge modules or processes running on the edge device. The actual memory and CPU requirements for Azure SQL Edge will vary based on the complexity of the workload and volume of data being processed. When choosing a hardware for your solution, Microsoft recommends that you run extensive performance tests to ensure that the required performance characteristics for your solution are met.

Azure SQL Edge components

Azure SQL Edge only supports the database engine. It doesn't include support for other components available with SQL Server 2019 on Windows or with SQL Server 2019 on Linux. Specifically, Azure SQL Edge doesn't support SQL Server components like Analysis Services, Reporting Services, Integration Services, Master Data Services, Machine Learning Services (In-Database), and Machine Learning Server (standalone).

Supported features

In addition to supporting a subset of features of SQL Server on Linux, Azure SQL Edge includes support for the following new features:

  • SQL streaming, which is based on the same engine that powers Azure Stream Analytics, provides real-time data streaming capabilities in Azure SQL Edge.
  • The T-SQL function call Date_Bucket for Time-Series data analytics.
  • Machine learning capabilities through the ONNX runtime, included with the SQL engine.

Unsupported features

The following list includes the SQL Server 2019 on Linux features that aren't currently supported in Azure SQL Edge.

Area Unsupported feature or service
Database Design In-memory OLTP, and related DDL commands and Transact-SQL functions, catalog views, and dynamic management views.
  HierarchyID data type, and related DDL commands and Transact-SQL functions, catalog views, and dynamic management views.
  Spatial data type, and related DDL commands and Transact-SQL functions, catalog views, and dynamic management views.
  Stretch DB, and related DDL commands and Transact-SQL functions, catalog views, and dynamic management views.
  Full-text indexes and search, and related DDL commands and Transact-SQL functions, catalog views, and dynamic management views.
  FileTable, FILESTREAM, and related DDL commands and Transact-SQL functions, catalog views, and dynamic management views.
Database Engine Replication. Note that you can configure Azure SQL Edge as a push subscriber of a replication topology.
  Polybase. Note that you can configure Azure SQL Edge as a target for external tables in Polybase.
  Language extensibility through Java and Spark.
  Active Directory integration.
  Database Auto Shrink. The Auto shrink property for a database can be set using the ALTER DATABASE <database_name> SET AUTO_SHRINK ON command, however that change has no effect. The automatic shrink task will not run against the database. Users can still shrink the database files using the 'DBCC' commands.
  Database snapshots.
  Support for persistent memory.
  Microsoft Distributed Transaction Coordinator.
  Resource governor and IO resource governance.
  Buffer pool extension.
  Distributed query with third-party connections.
  Linked servers.
  System extended stored procedures (such as XP_CMDSHELL).
  CLR assemblies, and related DDL commands and Transact-SQL functions, catalog views, and dynamic management views.
  CLR-dependent T-SQL functions, such as ASSEMBLYPROPERTY, FORMAT, PARSE, and TRY_PARSE.
  CLR-dependent date and time catalog views, functions, and query clauses.
  Buffer pool extension.
  Database mail.
  Service Broker
  Policy Based Management
  Management Data Warehouse
  Contained Databases
SQL Server Agent Subsystems: CmdExec, PowerShell, Queue Reader, SSIS, SSAS, and SSRS.
  Alerts.
  Managed backup.
High Availability Always On availability groups.
  Basic availability groups.
  Always On failover cluster instance.
  Database mirroring.
  Hot add memory and CPU.
Security Extensible key management.
  Active Directory integration.
  Support for secure enclaves.
Services SQL Server Browser.
  Machine Learning through R and Python.
  StreamInsight.
  Analysis Services.
  Reporting Services.
  Data Quality Services.
  Master Data Services.
  Distributed Replay.
Manageability SQL Server Utility Control Point.

Next steps