SQL with Manoj

 
Today on 4th November 2019 Microsoft in MSIgnite2019 event announced the release of new version of SQL Server i.e. SQL Server 2019.
 

New stuff in SQL Server 2019 is all about Big Data Clusters for SQL Server, which will allow you to:
– Deploy scalable clusters of SQL Server, Spark, HDFS on Kubernetes
– Read, write, and process big data from Transact-SQL or Spark
– With Polybase query data from external SQL Server, Oracle, Teradata, MongoDB, and ODBC data sources with external tables
– and many more, we will check below…

 
–> Download SQL Server (evaluation version):

To download SQL Server 2019 you can Register and Download the Full or Evaluation version (180 days) here.

Or you can directly download the installer SQL2019-SSEI-Eval.exe
 

–> Free Developer Version:

Back in March 2016 Microsoft announced that going forward the Developer version of SQL Server any release will be free for Developers and Learning purpose. Register and Download the Developer version.

This Developer version is meant for development and testing only, and not for production environments or for use with production data. For more info please check my previous blog post.
 

–> Download SSMS (separate install):

Microsoft starting with SQL Server 2016 decoupled SSMS from SQL Server setup and is available as a separate installer. This is basically to support the move to make a universal version of SSMS for both SQL Server on-Prem & Azure SQL Database, that will ship every month or so. The SSMS setup is available separately as free download.
 

–> Download SSRS (Reporting Services):

Just like SSMS, now SSRS is also separately available for install from Microsoft Download Center, link.
 

–> Check new features in SQL Server 2019:

1. Big data clusters with scalable compute and storage composed of SQL Server, Spark, and HDFS. It provides key elements of a data lake – Hadoop Distributed File System (HDFS), Spark, and analytics tools deeply integrated with SQL Server. [more info]

2. A complete Data Science & AI platform to train and operationalize models in SQL Server ML Services or Spark ML using Azure Data Studio notebooks.

3. Data virtualization allows queries across relational and non-relational data without movement or replication. PolyBase enabled you to run a T-SQL query inside SQL Server to pull data from Hadoop and return it in a structured format—all without moving or copying the data.

4. Intelligent Query Processing improves scaling of queries and Automatic Plan Correction resolves performance problems. [more info]
  – Table variable deferred compilation
  – Batch mode on row store
  – T-SQL Scalar UDF inlining
  – Approximate QP (Approximate COUNT DISTINCT)
  – Memory grant feedback, row mode

5. In-memory improvements for analytics on operational data using HTAP. Higher concurrency and scale through persistent memory (PMEM). [more info]
– Hybrid buffer pool
– Memory-optimized TempDB
– In-Memory OLTP support for Database Snapshots

6. Greater uptime with more online indexing operations. [more info]

7. Data Discovery & Classification labeling for GDPR and Vulnerability Assessment tool to track compliance.

8. Support for your choice of Windows, Linux, and containers. SQL Server on Linux for Docker Engine [link].

9. High Availability with, five synchronous replica pairs, Secondary to primary replica connection redirection, Run Always On availability groups on containers using Kubernetes. [more info]

10. Accelerated Database Recovery [more info]

11. SQL Graph enhancements, support of MATCH predicates in a MERGE statement, SHORTEST_PATH inside MATCH, and support for derived tables or view aliases in graph match query.
 

Check all the above and many more new features of SQL Server 2019 in MSDN Blogs.