The SQL Server 2019 Community Technology Preview (CTP) 3.1 is announced on a monthly basis with great interest. Customers can download this free build, test this release's characteristics and previous releases, and give the feedback to engineering team.
SQL Server 2019, introduced last year, combines SQL Server with Apache SparkTM and Hadoop Distributed File System for a unique information platform that provides analytics and AI across all related and non-related information.
SQL Server 2019 will also offer a complete solution for virtualization of the data that enables customers to combine data sets directly via SQL Server across multiple databases. SQL Server 2019 remains to offer unparalleled safety and efficiency across all information with fresh improved Windows and Linux performance capabilities.
Review the fresh CTP 3.1 preview documentation in the SQL Server 2019 for more information.
Graph Database: This release expands the first version of the SQL Server 2017 graphic functionality. This release expands the capabilities with an original release of the shortest track calculation capacity in relation to the previously shipded ability to use big graphs as nodes and edges. Now, graph table supports several filegroups to enhance the efficiency and scale of large graph facilities.
Encrypted Query Processing: The Always Secure Encrypted encrypting function also has the ability to support indexes to speed up queries on encrypted enclaves. The application set should expand significantly so that it can not be viewed by the operator of SQL Server and the Azure SQL database, when it is fully encrypted with the application proprietor holding the encryption key.
This allows users to run apps on untrusted hosting systems with no access by database administrators to unencrypted plaintext information saved in the database. This functionality can be tested without using specific hardware by SQL Server, which supported both software and hardware enclosures.
The Big Data Cluster function remains to provide important features for the SQL Server 2019 original release. This month, the release expands the Apache SparkTM function, enhancing the capacity to read and write internal tables straight to the database, and a mechanism for calculating compute-intensive workloads independently from storage. Both improvements should facilitate the integration of Apache SparkTM workloads within your SQL Server setting and make every possible effort.
This month's release also involves MLeap learning machine extensions that allow you to train the Apache SparkTM template and then use it in the SQL Server via a new Java extensibility feature in SQL Server CTP 3.0.
It should make it easier for data scientists to write and then deploy models in SQL server production environments for both periodic training and complete production in one single environment against the trained model.