SQL server optimization

Course prerequisites

SQL relationships are the backbone of the relational database model. They let you structure data efficiently, enforce data integrity, and connect information in meaningful ways. By establishing primary keys, foreign keys, and using different types of relationships, you ensure that your database remains organized, consistent, and easy to query.

A primary key is essential for ensuring each row in a table is uniquely identifiable, preventing duplicate records, establishing relationships, and aiding in efficient data retrieval.

A foreign key is a fundamental tool for relating tables, ensuring that data remains consistent and meaningful. By referencing a primary key in another table, foreign keys help maintain the logical connections and integrity of your database’s data.

Choosing the right join depends on what data you want to include or exclude when querying related tables.

Isolation levels let you choose the trade-off between strict data consistency and higher concurrent throughput. Understanding and selecting the appropriate isolation level is crucial to designing robust, efficient database transactions.

A heap table is simply a table without a clustered index. While this can provide faster inserts in some scenarios, it often leads to less efficient retrieval unless proper indexing strategies or usage patterns are applied. As a rule of thumb, in SQL Server use clustered tables, unless you have a very good reason not to.

SQL temporary tables are a convenient, flexible tool for managing intermediate data and simplifying complex query operations within a session. Their transient nature keeps the permanent schema clean, and their similarity to regular tables allows for indexing, constraints, and performance tuning options.

SQL lock types—shared, exclusive, update, intent, schema, and bulk update—manage concurrent access to data. Each type serves a unique purpose, balancing concurrency and consistency. Understanding these locks, along with lock granularity and escalation, helps DBAs and developers optimize performance and reduce contention in multi-user database environments.

SQL statistics are essential components of query optimization. By providing the optimizer with knowledge about data distribution, they guide the choice of execution plans. Maintaining accurate and up-to-date statistics is crucial for sustaining optimal query performance and ensuring your database runs efficiently.

While there is no universally enforced standard, common best practices include starting with an identifiable prefix, incorporating the table and column names, and occasionally indicating index type. These conventions help streamline database management, troubleshooting, and collaboration within development and operations teams.

A columnstore index transforms how data is stored and accessed in the database. By storing data column by column rather than row by row, it delivers high compression, efficient CPU utilization, and dramatic performance improvements for large-scale analytical queries. This makes it an essential tool in modern business intelligence and data warehousing environments.

SQL JSON indexing is all about improving query performance against semi-structured JSON data stored in relational databases. By using techniques like computed/generated columns, specialized indexing methods (like GIN for jsonb in PostgreSQL or search indexes in Oracle), and careful index design, you can achieve significant performance gains when querying JSON fields

XML indexes transform XML data into a structured form that the database engine can navigate efficiently. By creating a primary XML index (and optionally secondary XML indexes), you enable the optimizer to resolve XML queries faster, reduce parsing overhead, and achieve better query performance. However, these benefits come at a cost in terms of storage and maintenance, so careful planning is essential to ensure the right balance between query performance and resource usage.

Optimizing tempdb involves proper configuration (multiple files, equal sizes, fast storage), leveraging built-in enhancements in newer SQL Server versions, and monitoring usage patterns. By reducing contention, improving I/O throughput, and right-sizing tempdb, you can achieve more consistent and faster performance across the entire SQL Server environment.

The maximum degree of parallelism (MAXDOP) is a server configuration option for running SQL Server on multiple CPUs. It controls the number of processors used to run a single statement in parallel plan execution.

Memory-optimized tables provide a pathway to significantly enhanced performance and scalability by running operations in memory, removing locking overhead, streamlining data structures, and enabling native code execution of frequently used logic.

SQL Server Resource Governor is a feature that you can use to manage SQL Server workload and system resource consumption. 

SQL hints are a tool for fine-tuning query performance by influencing the optimizer’s choices.