As enterprises move their data pipelines into the cloud, they experience the benefits of distributed storage and computing, such as flexible scaling, cost-savings from outsourcing in-house IT infrastructure, and maximized data availability.
Microsoft created its Azure cloud platform to leverage these benefits. Azure SQL Database is a key component of that platform. Many applications now use Azure SQL Database as part of their data strategy.
Microsoft Azure SQL Database is a cloud-based relational database service designed to offer better availability, durability, and scalability than on-premises databases.
Azure SQL Database offers extensive features and flexible options for a variety of business requirements.
Azure SQL Database allows users to avoid many aspects of management so they can focus on their data’s value. Built-in features include smart performance tuning based on learned usage patterns, automatic systems for improving reliability and data security, and various adaptive processes to keep hosted databases fast and available.
For businesses looking to modernize their data pipeline, Azure SQL Database managed instances provide frictionless, secure migration of apps from on-premises to the cloud, along with access to the Azure Resource Manager API for dynamic provisioning — all without the need to pay for additional hardware.
Azure SQL Database leverages all the benefits of a cloud platform: it promises virtually no downtime for databases it hosts, with a stated goal of 99.99% availability.
The high availability architecture insures data against failures and relieves users from having to think about maintenance or potential outages. This architecture is also highly resilient, allowing businesses to build robust apps using retry logic, preventing loss of functionality or connectivity in the event of errors.
Patches and upgrades are automatic and intelligently managed by instances, and Microsoft helps customers plan their own maintenance events, if needed.
Azure SQL Database offers two distinct database backup options. Point in Time Restore (PITR) saves a dynamically-sized history of databases with configurable retention periods. In case of mistakes or failures, this option allows users to fall back to a full version of their database as far as a month in the past.
You can also set up long-term retention (LTR) policies to preserve backups for as long as 10 years, again with various options for scheduling and retention periods.
Backup storage is supported for free by Azure in intervals of 7 to 35 days. Users can pay for expanded storage if they find a need for more granular or longer-term data retention.
Azure SQL Database integrates with other tools and platforms, including Microsoft offerings such as Azure Active Directory, the Microsoft Azure Portal, SQL Server Management Studio, Visual Studio Code, and Microsoft System Center. It can also work in tandem with open source tools like sql-cli, Cheetah, and Hadoop.
Microsoft provides REST APIs for Azure SQL Database to connect databases with a variety of web services and applications. Additionally, most features found in the Microsoft SQL Server codebase are available in Azure SQL Database.
Azure Resource Manager offers users templates to create and manage related services and resources from a single platform, including databases, servers, storage, and more.
Azure SQL Database scales both horizontally and vertically. Users can scale up instances and increase performance with a premium availability model, or scale out by adding database units or sharding, a process of horizontal partitioning that makes database management faster and easier.
Azure can automate this process for users, but also provides tools and APIs for fine-grained manual provisioning.
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Azure SQL Database includes protective systems and tools to keep stored information secure and permissions well-managed, from the network level to individual table rows.
Users can customize database firewall rules to prevent unauthorized traffic or incursion threats, set multiple layers of authentication and user authorizations, configure encryption and secure keys, and dynamically mask data to protect private and sensitive information.
Azure SQL Database also employs anomaly detection to discover attempted exploitation of or harm to data. Automatic classification systems send alerts that flag data that needs to be secured or better managed, and auditing tools provide an overview of database and user events.
Customers can use a standalone database or Elastic Pools to store and manage their data.
Standalone is the typical cloud database, with overall processing, memory, and input/output usage calculated as Database Transaction Units (DTU). The DTU-based purchase model is the simplest option for users hoping to get started quickly with Azure SQL Database.
In Elastic Pools, multiple databases can share DTUs. Elastic Pools are best-suited for databases that have low activity but occasional usage spikes, so the cost savings/DTU reduction of Elastic Pools is dependent on how many of these databases a user can place within them.
Microsoft offers three pricing tiers depending on the user’s anticipated performance needs:
A vCore-based managed instance purchasing model is also available for users who require more control, configurability, and transparency when allocating resources. This model allows users to split compute and storage scaling, and choose service tiers based on their hardware configurations.
Enterprises hoping to migrate their established legacy systems to the cloud are often challenged by confusing pricing, ensuring that performance and security do not suffer in a new system, and replicating big data. They need the ability to load big data quickly, cheaply, and reliably from transactional data stores like Azure SQL Database directly to analytical platforms like Azure SQL Data Warehouse. Tools like Stitch Data Loader are designed for moving and integrating data to cloud data warehouses.
If you’re using Azure SQL Database, or are considering a migration to the Azure platform, try Stitch for free today and begin building your own performant, modern data pipeline.