Today, we are announcing changes to SQL Server analytics which includes:
- Customer feedback
- Retirement of SQL Server 2019 Big Data Clusters
- Retirement of PolyBase scale-out groups
- Path forward
We continue to see increased migration to the cloud, with analytical workloads leading that charge.
Customers have indicated that analytics in the cloud best aligns to employee skillsets, deployment simplicity and manageability, and cloud flexibility and scalability.
When we first introduced cloud analytics in 2017, many were still investing in on-premises analytical workloads. Today, we offer a wealth of cloud-based services that provide users with similar functionality, including Azure Data Lake Storage (ADLS), Azure Synapse Analytics, Azure SQL, and Azure Machine Learning.
According to the Gartner® 2020 Data and Analytics survey:
- Analytics, BI, and data science are the most common use cases being accelerated to the cloud due to COVID-19. The organization needs faster delivery of analytics insights to take action. Cloud, with its fast provision and prototyping ability, is an ideal place to start analytics and data science initiatives to nimbly react to the fast pace of changes.¹
- In the 2020 Gartner Data and Analytics Cloud survey, 74 percent of organizations use or plan to use cloud for analytics, BI and data science.¹
Retirement of SQL Server Big Data Clusters
Today, we are announcing the retirement of SQL Server 2019 Big Data Clusters. All existing users of SQL Server 2019 with Software Assurance will be fully supported on the platform for the next three years, through February 28, 2025. This software will continue to be maintained through SQL Server cumulative updates until that time. In the latest version of SQL Server, we are engineering the best mix of on-premises and in-cloud relational workloads and connectivity to Azure Synapse Analytics for advanced analytics in a flexible, scalable, and integrated environment. Please see below and read our documentation on SQL Server Big Data Clusters to learn more.
Changes to PolyBase support in SQL Server
Today, we are announcing the retirement of PolyBase scale-out groups in Microsoft SQL Server. Scale-out group functionality will be removed from the product in SQL Server 2022. In-market SQL Server 2019, 2017, and 2016 will continue to support the functionality to the end of support for those products.
PolyBase data virtualization will continue to be fully supported as a scale-up feature in SQL Server.
Secondly, Cloudera (CDP) and Hortonworks (HDP) external data sources will also be retired for all in-market versions of SQL Server and will not be included in SQL Server 2022. Moving forward, support for external data sources will be limited to product versions in mainstream support by the respective vendor. You are encouraged to use the new object storage integration functionality available in SQL Server 2022.
In SQL Server 2022, users will need to configure their external data sources to use new connectors when connecting to Azure Storage. The table below summarizes the change:
|External Data Source||From||To|
|Azure Blob Storage||wasb[s]||abs|
|ADLS Gen 2||abfs[s]||adls|
The path forward
If you wish to run analytics on-premises, SQL Server 2022 also provides important new capabilities, building upon its data virtualization suite of connectors by providing object storage integration over REST APIs. We will also continue to invest in the Spark SQL connector to ensure first-class connectivity from Apache Spark to all our SQL products. Additionally, we continue to invest in expanding hybrid capabilities with Azure Arc-enabled data services.
Integrating SQL Server with cloud analytics solutions is a critical capability, which is why we are introducing Azure Synapse Link for SQL Server 2022, the latest release of SQL Server, which will be generally available to purchase later this year. This is a major investment in helping you realize cloud-scale analytics in near real-time on your operational data.
Our priority is to empower you with the tools and services that ensure SQL Server integrates seamlessly into the world of analytic workloads in the cloud by blending operational, analytical, and virtual use cases in our flagship database engine. Please contact your Microsoft account manager if you need assistance in exploring how Microsoft can best empower your analytical needs.
¹Gartner Inc.: Use Cloud to Compose Analytics, BI and Data Science Capabilities for Reusability and Resilience, Julian Sun, Joao Tapadinhas, June 10, 2021.
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