Overview


Simplify edge architecture and app development

Bring the security and performance of the Microsoft SQL engine to the edge with Azure SQL Edge running on ARM64 and x64 architecture. This productivity tool for edge computing combines new capabilities such as data streaming and time series with in-database machine learning and graph features. Develop your application once and deploy anywhere across the edge, your data centre and Azure.

 

Features 

  • Small-footprint container running in ARM- and x64-based devices in a connected, disconnected or hybrid environment
  • Built-in data streaming and time series, with in-database machine learning and graph features for low-latency analytics
  • Data processing at the edge to optimise bandwidth, reaction time and cost
  • Deployment and updates from Azure or your enterprise portal for consistent security and turnkey management​
  • Install and manage Azure SQL Edge on all your edge devices with minimal overhead
  • Create and deploy the container from a single management portal, and update the container and data schema based on your security-management and business needs
  • Use a single container for your local streaming, storage, and machine learning. Because the surface area is the same as Azure SQL Database and SQL Server running on-premises, SQL Edge extends a consistent application development and management experience to the edge​

Expand device architecture coverage to include ARM-based and x64-based architecture. Choose either Windows or Linux as your host and use Kubernetes to orchestrate your device infrastructure for better efficiency and automation. Run Azure SQL Edge connected, semi-connected or offline to support various edge environments.

 

Manage data at the edge with data streaming, time series data analysis and machine learning-based data inferencing. Analyse data while it’s being streamed using time-windowing, aggregation and filtering capabilities, and achieve deeper insights by combining different data types such as time series and graphs.

 

Detect anomalies and apply business logic at the edge using the built-in machine learning-based data inferencing capabilities. Train machine learning models in the cloud or on-premises using the language or toolkit of your choice and convert them using the Open Neural Network Exchange (ONNX) framework to perform real-time data inferencing at the edge.

Advanced security

  • Flexible high availability and disaster recovery
  • Data protection with Transparent Data Encryption (TDE) and Always Encrypted capabilities
  • Control access with role-based access control (RBAC) and attribute-based access control (ABAC)
  • Comply with security regulation with data classification​