Modern applications often demand lightning-fast performance from their databases, whether they’re handling large transactional workloads or complex analytical queries. SQL Server’s in-memory OLTP feature addresses these needs by using memory-optimized tables and natively compiled stored procedures to boost throughput and reduce latency. This post provides an overview of natively compiled stored procedures, how to create them, and best practices for performance monitoring and maintenance.
Category: Performance
Comparative Analysis: SQL Server on Linux vs. Windows for Production
For years, SQL Server was synonymous with the Windows operating system, a pairing that brought deep integration and mature ecosystem support. The arrival of SQL Server on Linux introduced a broader choice, allowing organizations to deploy Microsoft’s flagship relational database on an entirely different platform. Although both versions share the same core engine, technical differences persist in the way each handles process scheduling, I/O, security, and administration.
SQL Server 2019 and the Memory Grant
When SQL Server runs a query, it needs memory for operations like sorting and joining data. It also relies on memory during query compilation to hold intermediate plans while the Query Optimizer finds the best execution strategy. In parallel processing scenarios, the memory requirement grows even further. SQL Server manages this by pre-allocating memory for each query through the SQL Server Operating System (SQLOS). This process ensures that no single query can monopolize the server’s memory
Exploring Spinlocks and Latch Contention in SQL Server
High concurrency can expose subtle performance bottlenecks in SQL Server, particularly those stemming from spinlocks and latch contention. Both mechanisms exist to synchronize access to shared data structures, yet they operate differently and require distinct troubleshooting approaches. By recognizing how they work and knowing what causes them to overload a system, DBAs can reduce CPU spikes, timeouts, and overall application slowdowns.
Understanding and Resolving TempDB Contention in SQL Server
TempDB contention is a common challenge in SQL Server when running highly concurrent workloads. In this post, we will explore why it occurs, how to identify it, and some practical solutions—especially leveraging In-Memory OLTP and memory-optimized table variables.
Optimizing Table Width and Data Types in SQL Server
Organizing data effectively in SQL Server can be a juggling act. You may be tempted to make tables as all-encompassing as possible by giving columns very large data types or piling on extra fields for convenience. While this seems harmless in the short term, it can lead to heavier storage requirements, slower queries, and frequent obstacles when updating the schema. Narrower tables, carefully chosen data types, and a normalized design often work together to keep a database agile and efficient.
Handling Compatibility Level Changes During SQL Server Upgrades
Compatibility levels determine how certain features of SQL Server behave, allowing databases to maintain functionality even as the server itself evolves. However, changing compatibility levels requires careful consideration to balance the benefits of new features against the potential risks of disrupting existing applications. This blog explores the importance of handling compatibility level changes thoughtfully during SQL Server upgrades, highlighting the risks of making changes too hastily and the advantages of adopting new compatibility levels within a reasonable timeframe.
Leveraging SQL Server 2019’s Last Known Actual Query Plan for Troubleshooting
Troubleshooting production performance issues is often challenging because detailed query execution data can vanish before you realize there’s a problem. Many times, you end up piecing together incomplete clues from runtime statistics or the plan cache. Fortunately, SQL Server 2019 introduced a powerful feature to address this pain point: the Last Known Actual Query Plan.
Understanding Worker Threads vs. CPU Utilization in SQL Server
When managing SQL Server performance, it’s important to understand the relationship—and the distinction—between worker threads and CPU utilization. These are two separate metrics that can behave independently. For instance, you might experience high CPU utilization while still having available worker threads, or you could have all worker threads occupied even when CPU utilization is low. This post takes a look at SQL Server worker threads and CPU utilization.
SQL Server’s Query Store: Understanding Plan Forcing and Performance Optimization
The Query Store in SQL Server is a powerful feature that enables database administrators and developers to track and analyze query performance over time. By storing runtime statistics and execution plans, it provides invaluable insights into how queries behave and how they can be optimized. This blog looks into the mechanics of the Query Store, the necessity of plan forcing, and how to effectively use it to stabilize and enhance query performance.