Azure SQL Data Warehouse Microsoft decided to make use of the cloud, it proceeded to commit itself by turning its Azure services into enterprise-grade cloud-based solutions that integrate cutting-edge features like data management and analytics at its core.
One of the services that Microsoft is pushing with a lot of energy, is the Azure SQL Data Warehouse, a scalable database management service, blended with elastic data warehouse features.
Initially, Microsoft released the Azure SQL Data Warehouse for a short preview in the month of July 2015, subsequently following it up with a public preview in September 2015.
The Azure SQL Data Warehouse can be considered as one of Microsoft's latest offerings. It is a scalable, fully-managed cloud service, which is compatible with a variety of existing Microsoft products and SQL Server tools, as well as with top Azure features like Data Factory and Machine Learning.
The Azure SQL Data Warehouse, as revealed by Microsoft, can support a massive amount of data, which can range in the tune of petabytes. This big data can be scaled easily by users, who are looking to manage costs and control operations in an efficient manner.
In addition, Microsoft's cloud-based SQL database management model allows users the convenience of a 'pay-as-you-go' structure, which enables cost-effective options like paying for services only when it is required.
The Azure SQL Data Warehouse serves as a fundamental component in retrieving, processing, storing, and analyzing big sets of data.
This enables the deployment of machine learning and analytics, which leverage business intelligence - a 'must-have' feature in new-generation business environments.
The enterprise-ready database service, based in the cloud, provides global businesses with an end-to-end solution that incorporates a control node, an increased number of compute nodes, and highly-reliable storage, which help enterprises manage the exponential influx of Big Data dominating today's computing ecosystem.
The integrated control node of Azure SQL Data Warehouse accomplishes data movement processes and compute operations that are spread across the entire computing network.
Right at the centre of these operations, is Azure SQL Data Warehouse's Massively Parallel Processing (MPP) engine, which splits convoluted queries into coordinates and parallel processes that enable processing across several compute nodes.
The Azure compute nodes, driven by the SQL Database, perform the heavy task, especially when big data is loaded into the warehouse.
When a user makes a data query, the MPP divides the query and distributes it across numerous compute nodes, which instantly start working with its respective chunk, processing the assigned data and adding it to the storage.
After the nodes complete the processing of a query, they deliver the results to Azure SQL's control node that consequently aggregates the processed data.
The Azure SQL's compute nodes and the control node are also dependent on the Microsoft Data Movement Services (DMS) as well, which facilitates seamless data movement and communication between the compute nodes and the control node, making the implementation of aggregations and joins possible across various nodes.
Microsoft's Azure SQL Data Warehouse deploys a high-performance, enterprise-grade storage, known as the Azure Blob Storage. The compute nodes read and write directly from this Storage.
Enterprise data is safe and secure with Azure Blob, as the state-of-the-art storage is not impacted by abrupt pausing of computing services, restoring or backing up of data to Azure SQL's warehouse, or the scaling of data warehouse and storage services.
As per Microsoft, the Azure SQL Data Warehouse integrates high-class techniques and algorithms that support the Data Movement Services in transferring data securely and efficiently.
In addition, the top-of-the-line database service also utilizes a high-level query optimizer and complex statistics, which combinedly generate query programs and optimize the distribution of data.
The best part of the Azure SQL Data Warehouse is its elastic nature that enables speedy scalability with possibilities to manage storage resources and compute separately. This creates a win-win platform, where users pay for only what they need and when they need.
The computing side of Azure SQL Data Warehouse is founded on the principle of Data Warehouse Unit (DWU), that keeps track of computational resources like storage I/O, memory, and CPUs used across participating compute nodes.
Another key advantage of Microsoft Azure SQL Data Warehouse is its 'pause' feature, that allows users to pause the computing services when they don't require it.
The leading cloud database service also provides users the flexibility to cancel any running queries, or any assigned DWUs to the data warehouse, which enables the curtailment of unnecessary to compute fees when services are not being used. User data, however, remains safe and secure with Azure Blob Storage.
Microsoft's Azure SQL Data Warehouse, when combined with other Microsoft tools and services, offers an unprecedented performance that becomes a key differentiator between winners and losers.
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