Azure SQL Database Hyperscale

Discover how you can scale SQL Server up to 100 TB with no need to pre-provision storage resources. ABCloudz can help you take advantage of a really big, fast, and secure Azure SQL Database Hyperscale for your data management needs.

What is Azure SQL Database Hyperscale?

Azure SQL Database Hyperscale is a SQL-based and highly scalable cloud service tier for single databases. With its revolutionary cloud-born architecture which decouples compute, log and storage, Azure SQL Database Hyperscale provides you with up to 100 TB of storage. Moreover, it operates with low latency and allows for high throughput. Microsoft declares transaction throughput at 100 MBps and constant time read scale.

azure sql database hyperscale architecture diagram

Huge size

Microsoft designed Azure SQL Database Hyperscale for very large databases. Azure SQL Database Hyperscale grows in size by 1 TB up to 100 terabytes, while Amazon Aurora provides you with just 64 TB.

Very fast

Despite the huge size, Azure SQL Database Hyperscale works very fast. Backups in Hyperscale are nearly instantaneous and they don’t slow down database performance. In addition, the point-in-time restore of a multi-terabyte database will take just a couple of minutes, rather than hours or days.

Easy to set up

You can migrate an existing Azure SQL Database to the Hyperscale service tier with a simple alter database command. The operation lasts about 2 minutes for the 50 TB database.


Hyperscale stores the data in reliable Azure storage. This brings all those cool features like 99.99% availability, disaster recovery, and mission-critical high performance. Keep in mind triple replication of the key Hyperscale components, while all three page servers consist of two virtual machines for hot failover.


Every page server stores up to 1 terabyte of data. It acts as an independent database with its own compute power and duplicate replicas. Hyperscale automatically adds a new page server when the used space in existing page servers reaches 1 TB.


The Hyperscale pricing starts from $173 per month. Maintaining a live 50 TB Azure SQL Database Hyperscale will cost you a little over $300 per month. That’s definitely not an expensive offer for this kind of data storage.

Challenges we have seen migrating to Azure SQL Database Hyperscale

On paper, Hyperscale looks really impressive. However, with our hands-on experience, we discovered a number of limitations. Here are some of the challenges that we have experienced moving our customer’s workloads to Hyperscale.




Prepare your data

You need to assess your original database before trying to move it to Hyperscale

The migration will fail if a database file grows during migration due to an active workload and crosses the 1 TB per file boundary. So, you need to make sure that there is no update workload running when you decide to migrate to Hyperscale.

Also, you can’t migrate databases with in-memory objects to Hypercale. You should drop all in-memory objects and recreate them as non-in-memory objects prior the migration.

Time is money

Moving terabytes of your data to the cloud may last too long

Scaling your Azure SQL Database to Hyperscale takes a few minutes. However, migrating terabytes of your data from the on-premises data center to the cloud may take a while. This downtime may be unacceptable, so, you may need to consider using Azure Data Box.

For high-speed data to Azure Data Box or directly to Azure via ExpressRoute from your data center, you can use parallel data export and import operations.

Getting started

Leveraging Azure SQL Database Hyperscale looks like a very attractive offer. On the one hand, you don’t need to convert your database application code after migrating your SQL Server database to the Hyperscale service tier. On the other hand, there’s a lot of things you need to take care of before the migration.

We recommend starting with a thorough analysis of your existing environment with our in-house tools. After that we will create the future-state architecture design of your environment and then migrate your workloads to the Azure cloud.

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