Azure SQL Data Warehouse, Microsoft’s cloud-based data warehousing service, offers a compelling set of benefits such as higher analytical query performance, faster and easier scalability, and lower operational costs than traditional local data warehouses. For the company.
However, like other IT environments and processes, the “weakest link” may eventually set limits and not fully realize the potential benefits. For Azure SQL Data Warehouse, the weak link for many organizations is a cloud data migration process that is difficult to implement, slow to implement, and can withstand changes based on business needs.
Now that you know what Azure SQL Database is, what is Azure SQL Data Warehouse? SQL Server data warehouse function in the cloud. SQL Server Data Warehouse is a local feature of SQL Server. In Azure, this is a dedicated service that lets you create a data warehouse that can store large amounts of data, scale up and down, and be fully managed. Like Azure SQL Database, Azure SQL Data Warehouse is the one you created. Don’t worry about infrastructure or licenses.
Azure SQL Data Warehouse is often used as a traditional data warehouse solution. This means using the table and column data schema you designed and putting a lot of data into it. Data visualization tools such as PowerBI can connect to a data warehouse to query data and answer business questions in reports and charts.
Azure SQL Data Warehouse has features designed to process big data and provide it for deep analysis and visualization.
How Azure SQL Data Warehouse Works
Azure SQL Data Warehouse is designed for enterprise-level data warehouse implementations and stores large amounts of data (up to petabytes) in Microsoft Azure. Since MPP is used to process analytical queries, it can provide quick query results for large data sets. You can also integrate structured, unstructured, and streaming data into a cloud-based data warehouse using a single SQL-based view in relational databases and non-relational Big Data stores. Users can manage Azure SQL Data Warehouse using SQL Server Management Studio (SSMS) or write queries using Azure Data Studio (ADS).
DataSQL Data Warehouse uses PolyBase to directly query Big Data stores such as Hadoop systems. With Polybase, organizations can use standard T-SQL queries to import data into SQL Data Warehouse and provide a single SQL-based query surface for all data. SQL Data Warehouse uses column storage to store data in relational tables. This reduces data storage costs and improves query performance.
SQL Data Warehouse is based on a scalable architecture to distribute the calculation of data on several nodes. The Azure SQL Data Warehouse architecture separates compute and storage, allowing users to scale independently and only pay for the processing and storage the organization needs. Many features are built into Azure and can be used by creating an Azure SQL data warehouse
A cost-effective pay-as-you-go model for organizations that implement their own enterprise-level data warehouse.
Leverage Azure cloud and storage resources.
Scalable computing power.
System management is carried out by Microsoft.
Ability to improve performance and globalize.
A low-cost solution with the ability to expand and calculate storage. You can pause or resume the database in minutes.
Microsoft guarantees that Azure SQL Data Warehouse offers 99.9% uptime.
Full compliance with standards and regulations such as PCI-DSS, SOX, HIPAA.
Integrated advanced security such as connection security, authentication, authorization and encryption.
Data sovereignty in more than 30 regions of the world.
Adapt to the workload. If your workload is large, you can take advantage of the power of the cloud, but you can control the cost by reducing the cloud for smaller workloads. You can also reduce costs by suspending or stopping workloads
Built-in Smart Cache speeds up data access and query performance.
Use massive parallelism behind the architecture. This allows you to run up to 128 simultaneous requests at a time and improves performance over traditional on-premises SQL Server.
Seamlessly create analytical tasks and hubs in addition to native connectivity with data integration and visualization services.
Data at rest is protected by Transparent Data Encryption (TDE).
Integration with Azure Active Directory, Data Factory, Data Lake Storage, Databricks and Microsoft Power BI.
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