Microsoft announced the discharged 24th September 2018 of first CTP form of SQL Server vNext for instance SQL Server 2019 CTP 2.0.
As we know,Microsoft effectively settled Machine Learning feature by including R and Python support for Data Analytics and Scientists in SQL Server 2016 and 2017 .
In addition, by and by Microsoft has included Big Data capacities under a bound together arrange by including support for Apache Spark and HDFS in SQL Server 2019 which is offering assistance for administering and addressing unstructured data with sorted out/social data.
Thus giving you an out-of-box from beginning to end half breed information stage with different sorts of outstanding jobs needing to be done like OLTP, OLAP, DW/BI, Advance Analytics, Big Data and ML and AI on your information.
Additionally, much equivalent to the past SQL Server 2017 the new SQL Server 2019 adaptation will in like manner run both on Windows and Linux.
Download SQL Server 2019 CTP bits:
To download the SQL Server 2019 you can Download the Free assessment adaptation (180 days).
New Features and Enhancements:
- Convey Big Data bunches with SQL Server and Spark by utilizing Polybase [Read more ]
- Assemble and modify CCI on the web (Clustered ColumnStore Indexes)
- Resumable online record make activity to respite and resume later from where the activity was stopped or fizzled, rather than restarting from the earliest starting point.
- Column mode memory award criticism
- Surmised COUNT DISTINCT (for huge information situations)
- Clump mode on RowStore without ColumnStore list
- Table variable conceded assemblage (for better cardinality gauges)
- New DMV sys.dm_db_page_info framework capacity returns page data
- Database checked default setting for on the web and resumable DDL tasks (ELEVATE_ONLINE or ELEVATE_RESUMABLE)
- Continuously On Availability Groups – upto 5 synchronous copies (3 till now)
- New Polybase connectors or SQL Server, Oracle, Teradata, and MongoDB
- Backing for MERGE DML and Edge Constraints in SQL Graph
- Extended help for steady memory gadgets (by bypassing the capacity heap of the working framework utilizing proficient memcpy tasks)
- SQL Data Discovery and Classification [Read more ]