Azure SQL Database Edge

Maybe you are still getting up-to-speed with the whole concept of cloud computing. If so, I have a lot of sympathy for you because there is so much to learn and because cloud technologies advance so rapidly. Here’s one more important concept to add to that pile of things to learn—edge computing.

The good news is that edge computing is a technology designed to answer the very specific use-case of high-performance IoT applications. If you don’t have IoT applications in-house or your organization never will have them, then you can safely skip this discussion.

A New Data Processing Model: Edge Computing

One of the most significant impediments to very demanding cloud-based applications is the latency of making several hops across the internet backbone to your Microsoft Azure or Amazon AWS data center. Once there, the data is processed, and then it must be sent all the way back to the client. That is simply too slow a data-processing paradigm for a wide variety of applications, especially IoT applications such as connected/autonomous cars or security systems with facial recognition.

So, instead of sending all that data back and forth across the full internet backbone, why don’t we use distributed and decentralized computing resources (called “edge nodes”) to process that data at the very edge of the internet? Typically, some data will still need to move from the edge nodes back to the cloud data center, usually through a gateway or edge server. It’s also entirely possible that we might not even need to access the cloud. But if we do, our edge application will experience lower latency (because we’re sending a tiny fraction of the data we would have otherwise sent) and greatly reduced transmission, compute, and storage costs compared to a traditional cloud application since much of the computation is offloaded to the local edge computer.

Now Introducing Azure SQL Database Edge

Millions of developers worldwide are familiar with the SQL Server database engine and want Microsoft to provide them with a consistent programming experience no matter where their application resides, whether that be in the cloud, on-premise, or at the edge. As announced at the Build 2019 conference back in May 2019, Azure SQL DB Edge is a containerized package intended for both ARM and x86 powered devices, especially tailored for streaming and time-series data. It can be easily integrated into third-party IoT and edge products as well as Microsoft’s own edge models.

Read all of the details about the announcement here— It is now available in the Azure Marketplace via private preview, so you will need to answer a brief questionnaire to get access.

Here is what Azure SQL Database Edge offers:

  • Build once and deploy anywhere, including Azure SQL

Database, SQL Server, and Azure SQL Database Edge

  • Bi-directional data movement between the edge and on-premise or the cloud for an intelligent store-and-forward pattern
  • Strong security built into Azure SQL Database for fully encrypted data both at-rest and in-motion on edge nodes and edge gateways
  • Ability to combine data streaming and time-series with in-database machine learning to enable low latency analytics
  • Cloud connected and fully disconnected edge scenarios with local compute and storage. Management of the entire system from a central management portal from Azure IoT.
  • Support for existing data visualization tools such as Power BI and Tableau.
  • Full programmatic support for T-SQL language, as well as analytic support using R, Python, Java, and Spark.
  • Support for processing and storing graph, JSON, and time series data in the database, coupled with the ability to apply analytics and in-database machine learning capabilities on non-relational datatypes. This enables scenarios where you want to train your machine learning models in the cloud and score the at the edge node.

If you’re building IoT applications for the Microsoft Azure cloud, it is definitely worth your time to learn more about Azure SQL Database Edge!

You can get started with Azure SQL Database Edge by enrolling in the Early Adopter Program at