Description

Microsoft SQL Server 2019 is a powerful, enterprise-grade relational database management system (RDBMS) known for its robustness, scalability, and features supporting big data and advanced analytics. Here are some key aspects of SQL Server 2019:

1. Big Data Clusters

• SQL Server 2019 introduces Big Data Clusters, allowing users to deploy scalable clusters of SQL Server, Spark, and HDFS (Hadoop Distributed File System) containers running on Kubernetes. This feature helps manage and analyze large volumes of structured and unstructured data. It supports data virtualization, allowing access to external data sources like Oracle, MongoDB, and Teradata without moving the data.

2. Intelligent Query Processing (IQP)

• The Intelligent Query Processing suite in SQL Server 2019 optimizes query performance automatically, providing a series of enhancements like batch mode on rowstore, table variable deferred compilation, and approximate query processing.
• These features enhance performance for a wide range of queries, helping users avoid the need for extensive query tuning.

3. Data Virtualization and PolyBase

• With Data Virtualization, users can query and integrate external data sources like Oracle, MongoDB, and others directly from SQL Server without moving data. This feature relies on PolyBase, which has been expanded in SQL Server 2019 to support more external data sources.
• PolyBase enables the use of T-SQL to query external data as if it were part of the SQL Server, providing a seamless experience for users who need access to heterogeneous data sources.

4. Enhanced Security

• SQL Server 2019 builds on previous security features, including Always Encrypted with secure enclaves, which extends encryption for better security while enabling secure queries on encrypted data.
• Security features also include row-level security, dynamic data masking, and transparent data encryption.

5. In-Memory Database Capabilities

• The In-Memory OLTP (Online Transaction Processing) feature, introduced in earlier versions, continues to support performance gains in transactional workloads.
• It allows tables to be stored in memory for faster access, and Columnstore Indexes enhance performance for analytical queries.

6. High Availability and Disaster Recovery

• SQL Server 2019 includes Always On Availability Groups for high availability and failover support, which allow you to configure multiple database replicas.
• It also supports distributed transactions, synchronous and asynchronous commit modes, and secondary replicas for reading workloads.

7. Machine Learning Services

• SQL Server 2019 supports Machine Learning Services with R and Python integrated directly into the database. This enables the creation, training, and deployment of machine learning models close to the data, reducing the need for data movement and making ML workflows more efficient.
• Users can leverage Spark and HDFS capabilities in Big Data Clusters for large-scale machine learning.

8. Developer and Tooling Improvements

• SQL Server 2019 includes several enhancements for developers, such as support for JSON data, graph data processing, and UTF-8 encoding.
• SQL Server Management Studio (SSMS) and Azure Data Studio provide modern tools for managing SQL Server environments.

9. Containerization and Kubernetes Support

• SQL Server 2019 supports containerized deployments using Docker and orchestration with Kubernetes. This allows users to deploy SQL Server on-premises or in the cloud with increased flexibility.

10. Compatibility and Migration

• SQL Server 2019 is compatible with older versions of SQL Server, making it easier for organizations to upgrade.
• Migration tools like Database Migration Assistant (DMA) help streamline the process of migrating databases from other systems or older SQL Server versions.

Editions of SQL Server 2019

• SQL Server 2019 comes in various editions to suit different business needs:
  • Enterprise: For large-scale, mission-critical applications.
  • Standard: For mid-tier applications.
  • Express: A free, lightweight edition for smaller applications.
  • Developer: Free for development and testing (not for production use).

SQL Server 2019 represents a shift towards integrating big data and analytics capabilities directly within SQL Server while maintaining SQL Server’s reputation for reliability, security, and performance.

 Key Features Microsoft SQL Server 2019:

Microsoft SQL Server 2019 introduced several new features aimed at enhancing its capabilities for data management, analytics, and big data integration. Here’s a breakdown of the new features:

1. Big Data Clusters

• The most significant new feature in SQL Server 2019, Big Data Clusters allows SQL Server to handle large-scale data and integrates SQL Server with Apache Spark and HDFS (Hadoop Distributed File System).
• Provides data virtualization and data federation, letting users query across data sources like SQL Server, Oracle, MongoDB, and Teradata without moving the data.
• Simplifies complex big data scenarios by allowing users to query structured and unstructured data from one platform.

2. Intelligent Query Processing (IQP)

• Expands on the query optimization features from previous versions with a new suite of enhancements that optimize performance without requiring manual tuning.
• New capabilities within IQP include:
  • Batch Mode on Rowstore: Brings performance improvements to analytics on rowstore data.
  • Table Variable Deferred Compilation: Delays the compilation of table variables to provide better estimations and improve performance.
  • Approximate Query Processing: New functions like APPROX_COUNT_DISTINCT deliver faster results for big data sets by providing approximate counts, ideal for large aggregations.

3. Enhanced Security with Secure Enclaves

• Expands Always Encrypted with Secure Enclaves to enable computations on encrypted data in a secure area of memory. This feature provides more flexibility by allowing data to remain encrypted even during computations.
• Improves sensitive data protection without compromising on performance or functionality.

4. Data Virtualization via PolyBase Enhancements

• SQL Server 2019 expands PolyBase to support more external data sources, including Oracle, Teradata, MongoDB, and SAP HANA.
• With data virtualization, users can perform cross-database queries on external data sources from within SQL Server without moving or duplicating data.

5. In-Memory Database Enhancements

• Improvements to In-Memory OLTP for handling large volumes of transactions more efficiently by allowing tables and indexes to be stored in memory.
• New Persistent Memory Support helps reduce latency by directly accessing storage class memory.

6. Machine Learning Services Integration

• Introduces Machine Learning Services with support for R and Python directly within SQL Server, allowing advanced analytics close to the data.
• With Big Data Clusters, SQL Server 2019 allows the use of Spark and HDFS to handle larger datasets, enabling machine learning on massive data volumes.

7. High Availability and Disaster Recovery Improvements

• Enhancements to Always On Availability Groups allow for up to eight synchronous replicas and support for cross-database transaction support.
• Provides better options for high availability and disaster recovery in distributed environments.

8. Support for Kubernetes and Containerization

• SQL Server 2019 is designed for containerized deployments and supports Kubernetes as an orchestration layer, allowing easy deployment and scaling across on-premises, cloud, and hybrid environments.
• Container support streamlines SQL Server management across different platforms and environments.

9. Graph Data Processing Enhancements

• Building on the graph database features in earlier versions, SQL Server 2019 enhances Graph Data Processing to support more complex networked data analysis.
• Offers capabilities for handling complex relationships and hierarchical data for applications like social networks, fraud detection, and more.

10. Developer-Friendly Features

• JSON Enhancements: Improved JSON support allows easier data manipulation within JSON files.
• UTF-8 Support: Allows UTF-8 encoding for character data, reducing storage requirements and providing better support for multilingual applications.
• New Tools and Integration: SQL Server 2019 supports new versions of SQL Server Management Studio (SSMS) and Azure Data Studio for improved development and management experience.

11. Azure and Hybrid Cloud Integration

• SQL Server 2019 supports Azure Data Sync, Azure Blob Storage, and Azure Arc, enabling hybrid deployment models that span on-premises and cloud environments.
• Supports Azure Active Directory authentication, allowing SQL Server to integrate securely with Azure-based identity management.

SQL Server 2019 combines traditional database features with new capabilities in big data, data virtualization, and machine learning, giving users a versatile platform for modern data solutions. These features make it particularly well-suited for data-driven organizations looking to unify their data management and analytics across diverse sources and formats.