ML Capabilities In SQL Server 2019

SQL Server 2019 brings built-in ML capabilities and includes features related to R and Python.

Recently, Microsoft published some insights into ML capabilities inside of SQL Server 2019. These are built-in capabilities and include features related to R and Python.
 
Well, at the heart of it all is a solution called Big Data Clusters, which enables developers to create scalable clusters of SQL Server, Apache Spark, and HDFS containers running on Kubernetes.
 
 
 
Big Data Clusters offers flexibility in the ways you access the data and relational data side-by-side. Using the cluster, you can query data from external sources. It also enables you to store big data in HDFS managed by SQL Server.
 
SQL Server 2019 offers expanded machine learning capabilities built-in as well. You can add commonly required features related to the use of R and Python for machine learning.
 
For instance, SQL Server 2019 enables SQL Server ML Services to be installed on Linux. Failover clusters are supported for greater reliability. Additionally, improved scripting capabilities open new options for generating and enhancing models.
 
The integration of Python with the SQL server database engine allows developers to perform advanced ML tasks close to the data rather than moving it around. And, insights generated from the Python runtime are accessible by production applications using standard SQL Server data access methods.
 
Partition-based modeling allows you to train several small models instead of one large model when using partitioned data.
 
To learn more you can visit the official blog here.