Difference between SQL Server 2017 & 2019

SQL Server 2017 and SQL Server 2019 are both major releases of Microsoft's SQL Server database management system, each introducing significant features, improvements, and enhancements. Here are some key differences between SQL Server 2017 and SQL Server 2019:

1.       Big Data Clusters:

·  SQL Server 2019 introduces Big Data Clusters, a feature that combines SQL Server with Apache Spark and Hadoop Distributed File System (HDFS). It allows you to deploy scalable clusters of SQL Server, Spark, and HDFS containers running on Kubernetes.

·  SQL Server 2017 does not have native support for Big Data Clusters.

2.       Intelligent Performance:

·  SQL Server 2019 includes enhancements for intelligent performance tuning and optimization, such as the ability to automatically tune database performance using the Adaptive Query Processing feature.

·  While SQL Server 2017 has some performance tuning capabilities, SQL Server 2019 introduces more advanced and automated performance optimization features.

3.       Linux Support:

·  Both SQL Server 2017 and SQL Server 2019 support Linux platforms, allowing you to run SQL Server on Linux-based operating systems.

·  SQL Server 2019 may have additional improvements and optimizations for running on Linux compared to SQL Server 2017.

4.       Security Enhancements:

·  SQL Server 2019 introduces several security enhancements, including the ability to encrypt sensitive data with Always Encrypted with secure enclaves, which provides enhanced security for data at rest and in transit.

·  SQL Server 2017 also includes security features such as Always Encrypted, Transparent Data Encryption (TDE), and Row-Level Security (RLS), but SQL Server 2019 adds more advanced security capabilities.

5.       Big Data and Analytics Integration:

·  SQL Server 2019 enhances integration with big data and analytics platforms, such as support for Apache Kafka in SQL Server's PolyBase feature, enabling seamless data integration and querying across diverse data sources.

·  While SQL Server 2017 also supports integration with external data sources through PolyBase, SQL Server 2019 expands these capabilities with additional connectors and improvements.

6.       Enhanced Developer Tools:

·  Both SQL Server 2017 and SQL Server 2019 provide developer tools and enhancements, such as improved support for Python and R languages for data analysis and machine learning within SQL Server.

·  SQL Server 2019 may have updated versions or additional features in its developer tools compared to SQL Server 2017.