SQL Server 2019 is Microsoft’s enterprise-grade relational database engine that merges on-premises performance, intelligent query processing, built-in AI, and seamless big-data integration. It introduces features like Intelligent Query Processing, Accelerated Database Recovery, Always Encrypted with secure enclaves, and Big Data Clusters to simplify analytics across relational and Hadoop data.
SQL Server 2019 is Microsoft’s latest long-term-support release of its relational database management system, blending OLTP, analytics, and big-data processing under one license. It runs on Windows, Linux, Docker, and Kubernetes.
Upgrading delivers intelligent query processing, faster recovery from long transactions, in-database AI via Python/R, and simplified data virtualization across Oracle, MongoDB, and Hadoop without ETL.
Intelligent Query Processing (IQP) optimizes execution plans automatically, reducing CPU and memory usage for common workloads without code changes.
Accelerated Database Recovery (ADR) rewrites the engine’s logging and recovery paths, shrinking rollback time from minutes to seconds and slashing transaction log growth.
Always Encrypted with secure enclaves lets SQL Server decrypt data inside a protected memory region, enabling secure range searches and pattern matching on encrypted columns.
Data Classification and Vulnerability Assessment scan databases, recommend sensitivity labels, and track compliance.
A Big Data Cluster (BDC) deploys SQL Server, Spark, and HDFS containers on Kubernetes, unifying queries across relational tables and data lakes using PolyBase.
Run the SQL Server 2019 setup, choose the edition, accept the license, select Database Engine Services, configure mixed authentication, assign SA password, add administrators, then complete.
Import the Microsoft repository, install the mssql-server package, run sudo /opt/mssql/bin/mssql-conf setup to select edition and set SA password, then open port 1433.
Set database compatibility level to 150: ALTER DATABASE MyDB SET COMPATIBILITY_LEVEL = 150;. IQP activates automatically at that level.
SQL Server now waits until first execution to compile table-variable queries, using actual row counts instead of the old fixed estimate of one row, improving plan quality.
The optimizer rewrites scalar user-defined functions into relational expressions, eliminating row-by-row calls and boosting CPU efficiency dramatically.
After a query executes, SQL Server adjusts future memory grants based on actual consumption, preventing repeated spills or excessive allocations.
ADR introduces a persisted version store in each database, enabling instantaneous rollback and crash recovery by logically undoing only user transactions instead of scanning the entire log.
SQL Server 2019 supports up to five synchronous replicas with automatic seeding, configurable secondary replica read workloads, and Kubernetes-native deployment for flexible orchestration.
Create or rebuild large indexes using WITH (RESUMABLE = ON). You can pause and resume tasks, minimizing maintenance windows.
Create an external data source and external table pointing to Oracle, MongoDB, Teradata, or HDFS. Query them with standard T-SQL, joining to local tables without ETL.
Enable the Machine Learning Services feature, then execute sp_execute_external_script with language = 'Python'. Data stays in SQL Server memory, reducing movement.
Use Intelligent Performance dashboard in SSMS, Query Store for plan history, and Extended Events to capture query waits and system health.
SQL Server 2019 comes in Developer (free), Express (free, limited), Standard (core/Server+CAL), and Enterprise editions. Big Data Clusters require Enterprise.
SQL Server offers built-in ML, Windows authentication, and integrated ETL, whereas PostgreSQL emphasizes extensibility and open licensing. Performance depends on workload.
Set MAXDOP and cost threshold for parallelism, isolate TempDB to fast SSDs, enable Query Store, and schedule backups with CHECKSUM and VERIFYONLY.
SQL Server 2019 delivers automatic performance gains, stronger security, and hybrid analytics without leaving T-SQL. Upgrading lets teams modernize databases while keeping familiar tooling.
Yes. Big Data Clusters deploy SQL Server, Spark, and HDFS containers on Kubernetes, enabling scalable analytics and high availability.
The Developer and Express editions are free. Standard and Enterprise require licensing fees, with Enterprise unlocking advanced features like Big Data Clusters.
Microsoft provides 5 years of mainstream support and 5 years of extended support, ending January 2030.
No direct downgrade exists. Use exports or generate scripts to move data to older versions.
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