Overview



Real-time data insights for IoT servers, gateways, and devices

Azure SQL Edge, a robust Internet of Things (IoT) database for edge computing, combines capabilities such as data streaming and time series with built-in machine learning and graph features. Extend the industry-leading Microsoft SQL engine to edge devices for consistent performance and security across your entire data estate, from cloud to edge. Develop your applications once and deploy them anywhere across the edge, your on-premises datacenter, or Azure.

Built-in data streaming and time series, with in-database machine learning and graph features for low-latency analytics


 

Data processing at the edge for online, offline, or hybrid environments to overcome latency and bandwidth constraints


 

Deploy and update from the Azure portal or your enterprise portal for consistent security and turnkey management


 

Simplified pricing with no upfront cost and subscriptions offers as low as USD60 per year per device


 

 

Conduct real-time scoring at the edge with built-in AI

Detect anomalies and apply business logic at the edge using the built-in machine learning capabilities. Choose from popular machine learning languages and convert them using the Open Neural Network Exchange (ONNX) to process time-series, graph, and other types of data. Deploy your cloud-trained models onto edge servers, gateways, and devices to perform real-time analytics on streaming data.

 

Store and analyze time-series data

Stream, store, and analyze time-series data using a solution that’s optimized for edge workloads such as IoT. Analyze 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.

A screenshot from the Data Exposed video titled What is Azure SQL Edge.
 

Use your choice of platform online or offline

Run Azure SQL Edge in connected, disconnected, or hybrid environments. Expand device architecture coverage to include ARM-based and x64-based architecture. Choose either Windows or Linux as the operating system, and use Kubernetes to orchestrate your device infrastructure for better efficiency and automation.