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The cloud is becoming increasingly distributed, with container technologies allowing easy deployment of what had been cloud functionality to devices at the edge of the network. What began with function-as-a-service runtimes has now graduated to supporting PaaS tools and technologies, stretching the cloud platform from public hyperscale data centers down to low-cost devices running on your network.
Microsoft has been talking about “the intelligent cloud and the intelligent edge” for a long time now, with a focus on finding ways around the bandwidth crunch between data sources and data processing in cloud architectures. There’s a certain level of self-interest in this approach, with hyperscale data centers close to cheap power but a long way from metropolitan population densities and relatively cheap bandwidth. If power is cheap and data is expensive, then why not process it close to the source?
SQL Server everywhere
At the heart of much of Microsoft’s cloud platform is its SQL Server database, now grown into a family of databases that work across public and private clouds; at desktop, data center, and hyperscale; and on both Windows and Linux. That family of databases has recently been joined by a new member: Azure SQL Edge. Designed for IoT (Internet of Things) and edge gateway scenarios on Intel and ARM hardware, it’s a small, containerized database that can operate both while connected and disconnected, providing a place to preprocess and stream data that can be developed remotely and delivered and managed from Azure.
Like the rest of the SQL Server family, Azure SQL Edge is a relational database with nonrelational capabilities. You can use it for traditional table-based storage, or instead work with JSON documents, with graph content, or with time-series data. That combination ensures you can use it for many different roles, but with a focus on IoT applications. It’s built on the SQL Server engine so there’s no...