Microsoft SQL Server 2019

Microsoft SQL Server 2019 - 100% Online Activation with Microsoft Operating System.

This version of SQL Server Reporting Services features support for Azure SQL managed instances, Power BI Premium data sets, enhanced accessibility, Azure Active Directory application proxy, and transparent database encryption. It will also update Microsoft Report Builder. For more information, see What's new in SQL Server Reporting Services .SQL Server Reporting Services
   
New HTML control The HTML control replaces all previous Silverlight components. Silverlight dependencies have been removed.
Support for Azure SQL Database managed instance database Host Master Data Services on the managed instance . See Master Data Services installation and configuration .
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SQL Server Master Data Services
Flexible file source and target Read and write data to Azure Blob storage and Azure Data Lake Storage Gen2. See flexible file source and flexible file target .
Flexible file tasks Perform file operations on the local file system, Azure Blob storage, and Azure Data Lake Storage Gen2. View flexible file tasks .
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This version introduces new features that improve file operations.
SQL Server Integration Services
   
Online attach Online attach can be used to synchronize local read replicas in a scale-out environment. To learn more, see Online Attachment .
Power BI cache refresh control settings This release introduces the ClientCacheRefreshPolicy attribute, which will replace cached dashboard tile data and report data when the Power BI service initially loads Live Connect reports. For more information, see General properties .
Resource management property settings This version includes new memory settings: Memory \ QueryMemoryLimit for resource management, DbpropMsmdRequestMemoryLimit, and OLAP \ Query \ RowsetSerializationLimit. For details, see Memory settings .
Many-to-many relationship in tabular model Many-to-many relationships are allowed between tables, and the columns in both tables are non-unique. For more information, see Relationships in the table model .
Query cross Query cross is a table model system configuration that can improve user query response time under high concurrency. To learn more, see Query Cross .
Calculation group in tabular model By grouping common metric expressions into "calculated items", the calculation group can significantly reduce the number of redundant metric values. To learn more, see the calculation group in the tabular model .
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This release introduces new features and improvements for performance, resource management, and client support.
SQL Server Analysis Services
   
Windows Server Failover Cluster The high availability of machine learning services can be configured on a Windows Server failover cluster.
Partition-based modeling It can be used to add sp_execute_external_scriptnew parameters to process an external script for each data partition. This feature supports training multiple small models (one model per data partition) instead of one large model. See Creating a partition-based model .
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SQL Server Machine Learning Service
   
Server / CAL license product key setting warning If an enterprise server / CAL license product key is entered, and there are more than 20 physical cores on the computer, or 40 logical cores when hyperthreading is enabled, a warning will be displayed during the installation process. The user can still confirm the limit and continue setting, or enter a license key that supports the maximum number of processors in the operating system.
New parallelism setting options Set up the "maximum parallelism" server configuration during installation. For more information, see "Database Engine Configuration - MaxDOP" page , and install SQL Server from a command prompt in the parameters. The default value follows the maximum parallelism guidelines in the configuration server configuration option "Maximum Parallelism" . SQLMAXDOP
New memory setting options Set the "Minimum Server Memory (MB)" and "Maximum Server Memory (MB)" server configurations during installation. See "Database Engine Configuration - Memory" page , as well as from the command prompt to install SQL Server in , and parameters. The recommended value follows the memory configuration guidelines in the server memory configuration options . USESQLRECOMMENDEDMEMORYLIMITSSQLMINMEMORYSQLMAXMEMORY
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Installation options
   
PolyBase and machine learning support SQL Server 2019 (15.x) introduces new ways to use SQL Server containers, such as machine learning services and PolyBase. Check out some examples in SQL Server in the container GitHub repository .
Red Hat certified container image Starting with SQL Server 2019 (15.x) , you can run SQL Server containers on Red Hat Enterprise Linux.
Non-root container SQL Server 2019 (15.x) introduces the ability to create more secure containers by starting the SQL Server process as a non-root user by default . See Building and running SQL Server containers as a non-root user .
Microsoft Container Registry The Microsoft Container Registry now replaces Docker Hub with new official Microsoft container images, including SQL Server 2019 (15.x) .
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The easiest way to start using SQL Server is to use containers. SQL Server 2019 (15.x) is built on the innovations introduced in earlier versions and is designed to enable you to deploy SQL Server containers on new platforms in a more secure manner and gain more features.
container
   
Change data capture (CDC) support SQL Server 2019 (15.x) on Linux now supports change data capture (CDC).

PolyBase on Linux See Installing PolyBase on Linux for non-Hadoop connectors . See PolyBase type mapping .
TempDB improvements By default, a new installation of SQL Server on Linux will create multiple TempDB data files (up to 8 data files) based on the number of logical cores. This does not apply to in-place minor version or major version upgrades. The size of each TempDB file is 8 MB, and the auto-growth size is 64 MB. This behavior is similar to the default SQL Server installation on Windows.
Machine learning services on Linux See Installing SQL Server machine learning services (Python and R) on Linux .
OpenLDAP supports third-party AD providers Please refer to the tutorial: Using Active Directory Authentication with SQL Server on Linux .
Supports Microsoft Distributed Transaction Coordinator (MSDTC) See how to configure MSDTC on Linux .
Copy support See SQL Server replication on Linux .
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Linux
SQL Server 2019 (15.x) is built on the innovations already introduced in SQL Server 2017 (14.x) , designed to enable you to run SQL Server on the platform of your choice and gain more features and Higher security.
Platform selection
   
Pause and resume the initial scan of transparent data encryption (TDE) See Transparent Data Encryption (TDE) Scanning-Pause and Resume .
Resumable online row storage index generation See Performing index operations online .
Online clustered column storage index generation and regeneration See Performing index operations online .
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Resumable operation
   
Accelerate database recovery Reduce recovery time after restarting or rolling back long-running transactions by accelerating database recovery (ADR). See Speeding up database recovery .
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restore
   
HADR equity Every Software Assurance customer of SQL Server will be able to use three enhancements to any version of SQL Server that Microsoft still supports. For more information, please see the announcement here .
Secondary copy to primary copy connection redirection Allows client application connections to be directed to the primary copy regardless of the target server specified in the connection string. For more information, see Secondary Replica to Primary Replica Read / Write Connection Redirection (AlwaysOn Availability Group) .
Up to five synchronized copies SQL Server 2019 (15.x) increased the maximum number of synchronized copies from 3 in SQL Server 2017 (14.x) to 5. You can configure 5 copies of this group for automatic failover in this group. There is 1 primary copy and 4 synchronized secondary copies.
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Availability Group
Every user needs to perform a common task when deploying SQL Server , which is to ensure that all mission-critical SQL Server instances and their databases are readily available when needed by the enterprise and end users. Usability is a key pillar of the SQL Server platform, and SQL Server 2019 (15.x) introduces many new features and enhancements that enable companies to ensure that their database environments are highly available.
High availability
   
SQL Server audit In addition, the audit conducted intensive treatment, including in the audit log data_sensitivity_informationnew field that contains the actual data returned by a query sensitivity classification (label). See for details and examples . ADD SENSITIVITY CLASSIFICATION
It is easier to identify the location of sensitive data in the enterprise, so that administrators can take the right measures to protect the database
Various security schemes, such as monitoring (auditing) and alerts for abnormal access to sensitive data
Help meet data privacy standards and regulatory compliance requirements
Data discovery and classification The data discovery and classification function provides the function of classifying and marking the columns in the user table. Classification of sensitive data (such as business, finance, medical, PII, etc.) plays a key role in the organization's information protection. It can serve as an infrastructure for:
Certificate management in SQL Server Configuration Manager You can now use SQL Server Configuration Manager to perform certificate management tasks such as viewing and deploying certificates. See Certificate Management (SQL Server Configuration Manager) .

Always Encrypted with Secure Enclave Extend Always Encrypted with in-situ encryption and rich computing by enabling computing on plain text data in the server-side security quarantine. In-situ encryption can improve the performance and reliability of encryption operations such as encrypted columns, rotated columns, and encryption keys, because it can avoid moving data out of the database. Support for rich computing (pattern matching and comparison operations) can unlock Always Encrypted to a wider set of scenarios and applications that require sensitive data protection and also require richer use in Transact-SQL queries Function. See Always Encrypted with Security Enclave .
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SQL Server provides a secure architecture designed to enable database administrators and developers to create secure database applications and respond to threats. Each version of SQL Server has been improved on the basis of the earlier version, and new features and functions have been introduced. SQL Server 2019 (15.x) continues to build on this basis.
Mission critical security
   
Detailed truncation warning Data truncation error messages include table and column names and truncated values by default. See VERBOSE_TRUNCATION_WARNINGS .
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When the extract, transform, and load (ETL) process fails because the source and target do not have matching data types and / or lengths, troubleshooting can be time-consuming, especially in large data sets. With SQL Server 2019 (15.x), you can learn more about data truncation errors more quickly.
wrong information
   
See the sys.spatial_reference_systems view for the definition of the new SRID .
7844 represents geographic 3D
7843 represents geographic 2D
New spatial reference identifier (SRID) Australian GDA2020 provides more reliable and accurate data, which is closer to the data provided by the global positioning system. The new SRID is:


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space
   
Register an external language CREATE EXTERNAL LANGUAGEIt is a new data definition language (DDL) that can register external languages (such as Java) in SQL Server. See CREATE EXTERNAL LANGUAGE .
SQL Server language extension Use an extensibility framework to execute external code. See SQL Server language extension .
New default Java runtime SQL Server now includes Azul System's Zulu Embedded, which is used to provide Java support throughout the product. Please refer to Free supported Java in SQL Server 2019 is now available (SQL Server 2019 is now available for free support of Java).
Support for Java data types See Java data type .
Java language SDK is open source The Microsoft Extensibility SDK for Microsoft SQL Server for Java is currently open source and available on GitHub .
New Java language SDK Simplified the development of Java programs that can be run from SQL Server. See SQL Server's Microsoft Extensibility SDK for Java .
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Language extension
   
Support UTF-8 character encoding Support UTF-8 for import and export encoding, and used as a database-level or column-level collation of string data. Support includes PolyBase external tables and Always Encrypted (when not used in Enclave). See collation and Unicode support .
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Supporting businesses in different countries / regions and regions, where the requirement to provide global multilingual database applications and services is essential to meet customer needs and meet specific market specifications
Unicode support
   
Use derived table or view aliases in graph matching queries See graph matching query .
Partitioned tables and indexes The graphics are now supported in table and index partitions.
New graphics function- SHORTEST_PATH Now it can be used MATCHin SHORTEST_PATHto find the shortest path between any two nodes in the graph, or for any length traversed.
Edge constraint cascade delete operation It is now possible to define cascading delete operations on edge constraints in the graph database. See edge constraint .
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Graphics
SQL Server 2019 (15.x) continues to provide a first-class developer experience, and enhanced graphics and spatial data types, UTF-8 support, and a new extensibility framework that enables developers to use the language of their choice to obtain all of their Data insights.
Developer experience
   
sys.dm_db_page_info(database_id, file_id, page_id, mode) The new DMF returns information about the pages in the database. See sys.dm_db_page_info (Transact-SQL) .
query_post_execution_plan_profile Extended Events, light analysis collected the equivalent of the actual implementation of the plan, and based on the use of standard analyzes query_post_execution_showplandifferent. See Query Analysis Infrastructure .
LAST_QUERY_PLAN_STATS The new database-wide configuration can be enabled sys.dm_exec_query_plan_stats. See ALTER DATABASE SCOPED CONFIGURATION .
sys.dm_exec_query_plan_stats The new dynamic management function (DMF) can return the equivalent value of the latest known actual execution plan of all queries. See sys.dm_exec_query_plan_stats .
sys.dm_exec_requests Column command If you SELECTwait for synchronization statistics update operation is complete before continuing to execute the query is displayed SELECT (STATMAN). See . sys.dm_exec_requests
LIGHTWEIGHT_QUERY_PROFILING New database scope configuration. See . LIGHTWEIGHT_QUERY_PROFILING
Query stored custom capture strategy When this policy is enabled, additional query storage configurations are available under the new "Query Storage Capture Policy" setting, which can be used to fine-tune data collection on specific servers. See ALTER DATABASE SET option .
WAIT_ON_SYNC_STATISTICS_REFRESH sys.dm_os_wait_statsNew wait types in the dynamic management view. It shows the cumulative time at the instance level for refresh operations on synchronization statistics. See . sys.dm_os_wait_stats
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Monitoring improvements allows you to unlock performance insights for any database workload whenever you need it.
Monitor
   
Scheduler worker role migration With worker role migration, idle schedulers can migrate worker roles from the runnable queues of other planners on the same NUMA node, and immediately resume the tasks of migrated worker roles. In the case where long-running tasks happen to be assigned to the same scheduler, this enhancement provides more balanced CPU usage. For more information, see SQL Server 2019 Smart Performance-Worker Role Migration .
Concurrent PFS update Page Free Space (PFS) pages are special pages in database files that SQL Server uses to help locate available space when allocating space for objects. Page latch contention on PFS pages is usually associated with TempDB , but when there are many concurrent object allocation threads, it may also occur on the user database. This improvement changes the way that PFS updates are used to manage concurrency so that they can be updated under shared latches (rather than exclusive latches). As of SQL Server 2019 (15.x) , this behavior is enabled by default in all databases (including TempDB).
Indirect checkpoint scalability See Improved indirect checkpoint scalability .
Reduced recompilation of workload By reducing unnecessary recompilation, the performance of using temporary tables across multiple scopes has been improved. See Recompilation with reduced workload .

Resource control REQUEST_MAX_MEMORY_GRANT_PERCENTAnd ALTER WORKLOAD GROUPa CREATE WORKLOAD GROUPconfigurable option value changes from integer to floating-point data type, to allow finer control of the memory limit. See Modifying workload groups and Creating workload groups .


Force fast forward and static cursor Provides mandatory support for query storage plans that move forward quickly and static cursors. See plan to force fast forward and static cursor support .
OPTIMIZE_FOR_SEQUENTIAL_KEY In the SQL Server database engine optimization is enabled within, help to improve the index high throughput concurrent inserts. This option is intended for indexes that are prone to contention for the last page insertion, which is common in indexes with sequential keys (such as identity columns, sequences, or date / time columns). See Creating an index .
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SQL Server 2019 (15.x) is built on the innovation of the earlier version of the intelligent database, and is designed to ensure increased operating speed . These improvements help overcome known resource bottlenecks and provide options to configure the database server to provide predictable performance across all workloads.
Intelligent performance
   
In-memory OLTP support for database snapshots SQL Server 2019 (15.x) introduced support for creating database snapshots of databases containing memory-optimized filegroups .
Memory optimized TempDB metadata SQL Server 2019 (15.x) introduces a new feature that belongs to the in- memory database feature family Memory Optimized TempDB Metadata, which can effectively eliminate this bottleneck and unlock a new level of scalability for TempDB's heavy workloads. In SQL Server 2019 (15.x) , system tables involved in managing temporary table metadata can be moved to non-persistent memory-optimized tables without latches. See Memory optimized TempDB metadata .
Mixed buffer pool The new feature of the SQL Server database engine allows direct access to database pages located in database files on persistent memory (PMEM) devices when needed. See mixed buffer pool .
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SQL Server in- memory database technology utilizes modern hardware innovations to provide unmatched performance and scale. SQL Server 2019 (15.x) is built on early innovations in this area (such as in-memory online transaction processing (OLTP)) and is designed to achieve a new level of scalability for all database workloads.
Memory Database
   
Use APPROX_COUNT_DISTINCTapproximate query processing For absolute accuracy is not important, but the response speed is critical circumstances, APPROX_COUNT_DISTINCTto use than COUNT(DISTINCT())fewer resources while aggregation across large data sets, in order to achieve high-level concurrency. See approximate query processing .
Table variable delayed compilation Improve the plan quality and overall performance of queries referencing table variables. During optimization and initial compilation, this function propagates cardinality estimates based on the actual table variable row count. This accurate line count information can optimize downstream planning operations. See Table Variable Delayed Compilation .
Scalar UDF inline Automatically convert scalar UDFs to relational expressions and embed them to call SQL queries. This conversion improves the performance of workloads that utilize scalar UDFs. See scalar UDF inlining .
Batch mode on line storage Support batch mode execution without using column storage index. Batch mode execution uses the CPU more efficiently during analysis workloads, but in versions lower than SQL Server 2019 (15.x) , it is only used when the query contains operations with column storage indexes. However, some applications may use features that are not supported by the column storage index, and therefore cannot use the batch mode. Starting with SQL Server 2019 (15.x) , batch mode is enabled on eligible analytical workloads whose queries include operations with any type of index (row storage or column storage). See batch mode on row storage .
Row mode memory grant feedback By adjusting the memory grant size of batch mode and row mode operators, the memory grant feedback function of batch mode was expanded. This adjustment can automatically correct over-grants, which can result in wasted memory and reduced concurrency. This adjustment can also correct insufficient memory grants (which can cause expensive overflow to disk). See row mode memory grant feedback .
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Through intelligent query processing , you can find that the performance of key parallel workloads has been improved when they are run on a large scale. At the same time, they can still adapt to the changing world of data. By default, smart query processing is supported on the latest database compatibility level settings, which will have a wide impact and can improve the performance of existing workloads with minimal implementation effort.
Intelligent query processing
SQL Server 2019 (15.x) is built on innovations in earlier versions and is designed to provide industry-leading performance out of the box. From intelligent query processing to support for persistent memory devices, the SQL Server intelligent database feature improves the performance and scalability of all database workloads without changing the application or database design.
Intelligent database


For details, see What is SQL Server Big Data Cluster .
   
Data virtualization with PolyBase Use external tables to query data from external SQL Server, Oracle, Teradata, MongoDB, and ODBC data sources . UTF-8 encoding support is now provided . For details, see What is PolyBase? .

 

Scalable big data solutions Deploy a scalable cluster of SQL Server, Spark, and HDFS containers running on Kubernetes. Read, write, and process big data in Transact-SQL or Spark. Easily merge and analyze high-value relational data through large-capacity big data. Query external data sources. Store big data in HDFS managed by SQL Server. Query data from multiple external data sources through a cluster. Use the data for AI, machine learning, and other analytical tasks. In the big data cluster in deploying and running applications . The primary instance of SQL Server uses Always On availability group technology to provide high availability and disaster recovery for all databases.
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Contemporary enterprises usually control huge data assets composed of various growing data sets hosted in isolated data sources throughout the company. With SQL Server 2019 SQL Server 2019 big data cluster , you can get near real-time insights from all the data, the cluster provides a complete environment to process large amounts of data including machine learning and AI functions.
Data virtualization and SQL Server 2019 big data cluster

 

Microsoft Windows SQL 2019 OEM KEY CODE 100% Online Activation with Orignal Microsoft Operating System