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SQL Server 2019 Preview Creates Unified Data Platform with Apache Spark Releases

Microsoft at the Ignite conference, announced the latest edition of its flagship RDBMS, SQL Server 2019 Preview and that it creates a unified data platform with Apache Spark and Hadoop Distributed File System (HDFS) packaged together with SQL Server.

“SQL Server 2019 will include Apache Spark and Hadoop Distributed File System (HDFS) for scalable compute and storage,” Microsoft said.

This new integrated architecture called as a “big data cluster.”

Microsoft says the new relational database management system will let customers manage their relational and non-relational databases in one offering.

“With SQL Server 2019, you can take on any data project, from traditional SQL Server workloads like OLTP, Data Warehousing and BI, to AI and advanced analytics over big data.”

Somewhat like SQL Server 2017, v2019 comes with some minor enhancements with one major new feature.

With this release of SQL Server, PolyBase has improved so that it has connectors to more data sources, including “Azure SQL Data Warehouse, Azure Cosmos DB, Mongo DB, Oracle, Teradata, MongoDB, PosgreSQL”, and others.

An image below shows data sources integrated by PolyBase in SQL Server 2019:

data sources that can be integrated by polybase in sql server 2019

Users can use T-SQL to query all of their SQL Server databases, so they can “break down data silos and easily combine their data from many sources using virtualization to avoid the time, effort, security risks and duplicate data created by data movement and replication.”

Because big data clusters deployed as containers on Kubernetes, it offers a consistent management and deployment experience on a variety of platforms on-premises and in the cloud: “OpenShift or Kubernetes on premises, Azure Kubernetes Service (AKS), Azure Stack (on AKS) and OpenShift on Azure.”

Users will have access to SQL Server Machine Learning Services and Spark Machine Learning, so they’ll get insights on all of their data, again, regardless of what form that data comes in.

HDFS, Spark, Knox, Ranger, Livy can also be quickly and easily deployed as Linux containers on Kubernetes.

Data can be easily ingested via Spark Streaming or traditional SQL inserts and stored in HDFS, relational tables, graph, or JSON/XML.

Data can be prepared by using either Spark jobs or Transact-SQL (T-SQL) queries and fed into machine learning model training routines in either Spark or the SQL Server master instance using a variety of programming languages, including Java, Python, R, and Scala.

Azure Data Studio announced now offers built-in support for SQL Server on-premises and Azure SQL Database, along with preview support for Azure SQL Managed Instance and Azure SQL Data Warehouse.

Previously released under the preview name SQL Operations Studio, “Azure Data Studio offers a modern editor experience with lightning fast IntelliSense, code snippets, source control integration, and an integrated terminal.”

It’s a free tool that runs on Windows, macOS, and Linux, for managing SQL Server, Azure SQL Database, and Azure SQL Data Warehouse; wherever they’re running.

SQL Server Management Studio 18.0 Preview will also be available for customers to continue managing SQL Servers with the support for SQL Server 2019 Public Preview.

Microsoft notes, over the course of time, it will integrate all the management features of SQL Server Management Studio into Azure Data Studio.

Here is an image of Azure Data Studio vs SQL Server Management Studio feature comparison:

azure data studio vs sql server management studio feature comparision

Also available now v2019 preview Linux-based container images on Microsoft Container Registry, Red Hat-Certified Container Images, and the SQL Server operator for Kubernetes.

SQL Server now leverages common programming languages with Java support in addition to already leveraging CLR, R, and Python. This new Java language extension allows calling a pre-compiled Java program and securely execute Java code on the same server with SQL Server.

SQL Server Machine Learning Services will now support clustering and allows to have a highly available intelligent database for both OLTP and Machine Learning scenarios.

Preview SQL Server 2019 for Windows, Linux, or Docker can be obtained from here.

And, to get started with new SQL Server big data features like data virtualizations and notebooks, download the Azure Data Studio here.

Microsoft also noted that SQL Server 2008 and SQL Server 2008 R2 end of support will happen during July 2019.


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