As the amount of data stored and queried continues to rise, it becomes increasingly important to have the most price-performant data warehouse. While we’re excited about being the industry leader in both of Gigaom’s TPC-H and TPC-DS benchmark reports, we don’t plan to stop innovating on behalf of our customers.
As Rohan Kumar mentioned in his blog on Monday, we’re excited to introduce several new features that will continue to make Azure SQL Data Warehouse the unmatched industry leader in price-performance, flexibility, and security.
To enable customers to continue improving the performance of their applications without adding any additional cost, we’re announcing preview availability of result-set caching, materialized views, and ordered clustered columnstore indexes.
In addition to price-performance enhancements, we’ve added new capabilities that enable customers to be more agile and flexible. The first is workload importance, which is a new feature that enables users to decide how workloads with conflicting needs get prioritized. Second, our new support for automatic statistics maintenance (auto-update statistics) means that manageability and maintenance of Azure SQL Data Warehouse just got easier and more effective. And finally, we’re also adding support for managing and querying JSON data. Users can now load JSON data directly into
We’re excited to share more ways to optimize your Azure costs. Today we are releasing the general availability of Azure SQL Data Warehouse reserved capacity and software plans for RedHat Enterprise Linux and SUSE.
Save up to 65 percent on your Azure SQL Data Warehouse workloads
Starting today, you can purchase Reserved Capacity for Azure SQL Data Warehouse and get up to a 65 percent discount over pay-as-you-go rates. Select from 1-year or 3-year pre-commit options.
Reserved capacity is purchased in increments of 100 cDWU. Multiple warehouses in the same region can use a single pool of Reserved Capacity. The fully elastic properties of the service remain and operations beyond the reserved capacity will be billed using pay-as-you-go pricing. As always, storage is charged separately from compute and will continue to be charged separately when purchasing Reserved Capacity.
More flexibility with exchanges and refunds
We’ve made it easy to exchange your reserved capacity and make other changes, like region or term. You can also cancel the reserved capacity at any time and get a refund (terms apply).
Next steps Visit the pricing page to learn more about Azure SQL Data Warehouse pricing. Purchase SQL Data Warehouse reserved capacity in the
Today, we want to call attention to the exciting news that Azure SQL Data Warehouse has again outperformed other cloud providers in the most recent GigaOm benchmark report.
This is the result of relentless innovation and laser-focused execution on providing new features our customers need, all while reducing prices so customers get industry-leading performance at the best possible value. In just the past year, SQL Data Warehouse has released 130+ features focused on providing customers with enhanced speed, flexibility, and security. And today we are excited to announce three additional enhancements that continue to make SQL Data Warehouse the industry leader:
Unparalleled query performance Intelligent workload management Unmatched security and privacy
In this blog, we’ll take a closer look at the technical capabilities of these new features and, most importantly, how you can start using them today.
Unparalleled query performance
In our March 2019 release, a collection of newly available features improved workload performance by up to 22x compared to previous versions of Azure SQL Data Warehouse, which contributed to our leadership position in both the TPC-H and TPC-DS benchmark reports.
This didn’t just happen overnight. With decades of experience building industry-leading database systems, like SQL Server, Azure SQL Data
We all want the truth. To properly assess your cloud analytics provider, ask them about the only three things that matter:
Independent benchmark results Company-wide access to insights Security and privacy What are their results on independent, industry-standard benchmarks?
Perhaps you’ve heard from other providers that benchmarks are irrelevant. If that’s what you’re hearing, maybe you should be asking yourself why? Independent, industry-standard benchmarks are important because they help you measure price and performance on both common and complex analytics workloads. They are essential indicators of value because as data volumes grow, it is vital to get the best performance you can at the lowest price possible.
In February, an independent study by GigaOm compared Azure SQL Data Warehouse, Amazon Redshift, and Google BigQuery using the highly recognized TPC-H benchmark. They found that Azure SQL Data Warehouse is up to 14x faster and costs 94 percent less than other cloud providers. And today, we are pleased to announce that in GigaOm’s second benchmark report, this time with the equally important TPC-DS benchmark, Azure SQL Data Warehouse is again the industry leader. Not Amazon Redshift. Not Google BigQuery. These results prove that Azure is the best place for all your analytics.
Today we’re announcing the public preview of Data Discovery & Classification for Azure SQL Data Warehouse, an additional capability for managing security for sensitive data. Azure SQL Data Warehouse is a fast, flexible, and secure cloud data warehouse tuned for running complex queries fast and across petabytes of data.
While it’s critical to protect the privacy of your customers and other sensitive data, it becomes unmanageable to discover, classify, and protect such sensitive data as your businesses and data assets are growing rapidly. The Data Discovery & Classification feature that we’re introducing natively with Azure SQL Data Warehouse helps alleviate this pain-point. The overall benefits of this capability are:
Meeting data privacy standards and regulatory compliance requirements such as General Data Protection Regulation (GDPR). Restricting access to and hardening the security of data warehouses containing highly sensitive data. Monitoring and alerting on anomalous access to sensitive data. Visualization of sensitive data in a central dashboard on the Azure portal. What is Data Discovery & Classification?
Data Discovery & Classification introduces a set of advanced capabilities aimed at protecting data and not just the data warehouse itself.
Auto-discovery and recommendations – Underlying classification engine automatically scans your data warehouse and identifies
Azure SQL Data Warehouse is a fast, flexible and secure analytics platform for enterprises of all sizes. Today we are announcing the preview availability of workload importance on the Gen2 platform to help customers manage resources more efficiently. Workload importance gives data engineers the ability to use importance to classify requests. Requests with higher importance are guaranteed quicker access to resources which helps meet SLAs.
“More with less” is often the motto when it comes to operating data warehousing solutions. The ability to easily scale up compute resources gives data engineers tremendous flexibility. However, when there is budget pressure and scaling down is required, problems can arise. Workload importance allows high business value work to meet SLAs in a shared environment with fewer resources.
An example of workload importance is shown below. The CEO’s request was submitted last and classified with high importance. Because the CEO’s request has high importance, it is granted access to resources before the Analyst requests allowing it to complete sooner.
Get started now classifying requests with importance
Classifying requests is done with the new CREATE WORKLOAD CLASSIFIER syntax. Below is an example that maps the login for the ExecutiveReports role to ABOVE_NORMAL importance and
Special thanks to Lee Schlesinger and the Talend team for their contribution to this blog post.
Following the significant announcement around the continued price-performance leadership of Azure Data Warehouse in February 2019, Talend announced support of Stitch Data Loader for Azure SQL Data Warehouse. Stich Data Loader is Talend’s recent addition to its offering portfolio small and mid-market customers. With Stitch Data Loader, customers can load 5 million rows/month into Azure SQL Data Warehouse for free or scale up to an unlimited number of rows with a subscription.
All across the industry, there is a rapid shift to the cloud. Utilizing fast, flexible, and secure cloud data warehouse is an important first step in that journey. With Microsoft Azure SQL Data Warehouse and Stitch Data Loader companies can get started faster than ever. The fact that ADW can be up to 14x faster, and 94 percent less expensive than similar options in the marketplace, should only help further accelerate adoption of cloud scale analytics by customers of all sizes.
Building pipelines to the cloud with Stitch Data Loader
The Stitch team built the Azure SQL Data Warehouse integration with the help of Microsoft engineers. The solution leverages Azure Blob Storage
When your Azure resources go down, one of your first questions is probably, “Is it me or is it Azure?” Azure Service Health helps you stay informed and take action when Azure service issues like incidents and planned maintenance affect you by providing a personalized health dashboard, customizable alerts, and expert guidance.
In this blog, we’ll cover how you can use Azure Service Health’s personalized dashboard to stay informed about issues that could affect you now or in the future.
Monitor Azure service issues and take action to mitigate downtime
You may already be familiar with the Azure status page, a global view of the health of all Azure services across all Azure regions. It’s a good reference for major incidents with widespread impact, but we recommend using Azure Service Health to stay informed about Azure incidents and maintenance. Azure Service Health only shows issues that affect you, provides information about all incidents and maintenance, and has richer capabilities like alerting, shareable updates and RCAs, and other guidance and support.
Azure Service Health tracks three types of health events that may impact you:
Service issues: Problems in Azure services that affect you right now. Planned maintenance: Upcoming maintenance that
Special thanks to Rik Tamm-Daniels and the Informatica team for their contribution to this blog post.
With the latest release of Azure SQL Data Warehouse, Microsoft doubles-down on Azure SQL DW as one of the core data services for digital transformation on Azure. In addition to the fundamental benefits of agility, on-demand scaling and unlimited compute availability, the most recent price-to-performance metrics from the GigaOM report are one of several the compelling arguments they have made for customers to adopt Azure SQL DW. Interestingly, Microsoft is also announcing the general availability of Azure Data Lake Gen 2 and Azure Data Explorer. Along with Power BI for rich visualization, these enhanced set of capabilities cement Microsoft’s leadership position around Cloud Scale Analytics.
Every day, I speak with joint Informatica and Microsoft customers who are looking to transform their approach to their data estate with a cohesive data lake and cloud data warehousing solution architecture. These customers range from global logistics companies, to auto manufacturers to the world’s largest insurers, and all of them see the tremendous potential of the Microsoft modern data estate approach; in fact, just via Informatica’s iPaaS (integration platform-as-a-service) offering, Informatica Intelligent Cloud Services, we’ve seen a
As Julia White mentioned in her blog today, we’re pleased to announce the general availability of Azure Data Lake Storage Gen2 and Azure Data Explorer. We also announced the preview of Azure Data Factory Mapping Data Flow. With these updates, Azure continues to be the best cloud for analytics with unmatched price-performance and security. In this blog post we’ll take a closer look at the technical capabilities of these new features.
Azure Data Lake Storage – The no compromise Data Lake
Azure Data Lake Storage (ADLS) combines the scalability, cost effectiveness, security model, and rich capabilities of Azure Blob Storage with a high-performance file system that is built for analytics and is compatible with the Hadoop Distributed File System. Customers no longer have to tradeoff between cost effectiveness and performance when choosing a cloud data lake.
One of our key priorities was to ensure that ADLS is compatible with the Apache ecosystem. We accomplished this by developing the Azure Blob File System (ABFS) driver. The ABFS driver is officially part of Apache Hadoop and Spark and is incorporated in many commercial distributions. The ABFS driver defines a URI scheme that allows files and folders to be distinctly addressed in the