Guest post by Tiffany Wissner, Senior Director, Data Platform
Yesterday at Microsoft’s Ignite conference, we demoed the first sneak peek of Azure SQL Data Warehouse. As you build more applications in the cloud and with the increase in cloud-born data, there is strong customer demand for a data warehouse solution in the cloud to manage large volumes of structured data and to process this data with relational processing for fast analytics. Customers also want to take advantage of the cost-efficiencies, elasticity and hyper-scale of cloud for their large data warehouses. They need for that data warehouse to work with their existing data tools, utilize their existing skills and integrate with their many sources of data.
To help address this need, last week at Build, we announced an enterprise-class elastic data warehouse in the cloud called Azure SQL Data Warehouse. There’s a number of distinctive features we’d like to highlight — including the ability to dynamically grow and shrink compute in seconds independent of storage, enabling you to pay only for the query performance you need. In addition customers can choose to simply pause compute so that you only incur compute costs when needed. The Azure SQL Data Warehouse service gives customers the ability to combine relational and non-relational data hosted in Hadoop using PolyBase.
Azure SQL Data Warehouse is a combination of enterprise-grade SQL Server augmented with the massively parallel processing architecture of the Analytics Platform System, which allows the SQL Data Warehouse service to scale across very large datasets. It integrates with existing Azure data tools including Power BI for data visualization, Azure Machine Learning for advanced analytics, Azure Data Factory for data orchestration and movement as well as Azure HDInsight, our 100% Apache Hadoop service for big data processing.
Here are five reasons why enterprises should choose Azure SQL Data Warehouse:
1) Enterprise-class cloud data warehouse built on SQL Server
SQL Data Warehouse extends the SQL Server family of products by extending the massive scale Analytics Platform System into the cloud. By offering an enterprise-class cloud data warehouse based on SQL Server, customers can take advantage of the developer skills and knowledge built over years working with the most widely deployed database in the world. The SQL Data Warehouse extends the T-SQL constructs you’re already familiar with to create indexes, partitions and stored procedures, which allows you to easily migrate to the cloud. With native integrations to Azure Data Factory, Azure Machine Learning and Power BI, customers are able to quickly ingest data, utilize learning algorithms, and visualize data born either in the cloud or on-premises. Watch the Build announcement video below for an overview of Azure SQL Data Warehouse and the integration of other Azure data services to help you gain insight into your business.
2) Separating compute and storage enables a data warehouse to meet your needs
Azure SQL Data Warehouse independently scales compute and storage so customers only pay for the query performance they need. Unlike other cloud data warehouses that require hours or days to resize for additional compute power, SQL Data Warehouse allows customers to grow or shrink query compute in seconds. Since compute and storage scale independently, costs are much easier to forecast when compared to other competitive offerings. SQL Data Warehouse offers the right balance of compute and storage to meet your needs when you need them. This means that as a customer you can scale your resources based as your needs grow rather than invest in infrastructure for the future.
3) Pause an instance to save costs
Dynamic pause enables customers to optimize the utilization of the compute infrastructure by ramping down compute while persisting the data. With other cloud vendors, customers are required to back up the data, delete the existing cluster, and, upon resume, generate a new cluster and restore data. This is both time consuming and complex for scenarios such as data marts or departmental data warehouses that need variable compute power.
4) PolyBase in the cloud makes combining data sets easy
With the incredible growth of all types of data, the need to combine structured and unstructured data is essential. With PolyBase, SQL Data Warehouse offers the ability to combine data sets easily. SQL Data Warehouse can query unstructured and semi-structured data stored in Azure Storage, Hortonworks Data Platform, or Cloudera using familiar T-SQL skills making it easy to combine data sets no matter where it is stored. Other vendors, follows the traditional data warehouse model that requires data to be moved into the instance to be accessible. SQL Data Warehouse allows the data to stay in Hadoop and combine the results with relational data via common T-SQL constructs. This keeps your data costs low and lets you choose the query speed that you need.
5) Hybrid infrastructure supports your needs on-premises and/or in the cloud
The SQL Data Warehouse service is an extension of the SQL Server family of products that offers an additional choice of data management to suit your business needs. Through support for a variety of first- and third-party products, the SQL Data Warehouse enables you to use the tools you use today to access, manage, manipulate and visualize data for faster insights. With SQL Data Warehouse you are able to quickly move to the cloud without having to move all of your infrastructure along with it. With the Analytics Platform System, Microsoft Azure and Azure SQL Data Warehouse, you can have the data warehouse solution you need on-premises, in the cloud or a hybrid solution.