Hi friends, in this article, we’ll be discussing about certain advanced SQL Server features and techniques, that can help experienced DBAs, to tune the SQL Server data platform even more, in terms of performance, security and scalability.
So, as an experienced SQL Server DBA, you are probably familiar with the fundamentals of SQL Server. There are, however, advanced features and techniques that you can use to improve performance, security, and scalability. We will look at some of these advanced features and techniques in this post.
1. Query Optimization Techniques
One of the most important tasks in the DBA’s daily routine, is query optimization. SQL Server queries can be optimized in a variety of ways. Among the techniques are:
- Query hints (learn more)
- Index creation and maintenance (learn more)
- Rewriting queries or advising developers to rewrite certain queries
- Table partitioning (learn more)
In addition to the above, DBAs can use the query store feature of SQL Server, to monitor query performance and identify queries that require optimization.
Moreover, you should definitely check what’s new in SQL Server 2019 and SQL Server 2022, since in these two versions of SQL Server, there have been added many features under the scope of intelligent query processing.
Feel free to check our courses on Udemy, “SQL Server 2022: What’s New – New and Enhanced Features” and “SQL Server 2019: What’s New – New and Enhanced Features” to check out what these features are, and see some relevant live demonstrations.
2. In-Memory OLTP Engine
The In-Memory OLTP feature in SQL Server, allows you to create memory-optimized tables and indexes, as well as, natively compiled stored procedures, which can improve query performance significantly.
The In-Memory OLTP engine in SQL Server, employs a distinct data storage engine optimized for memory-resident data. Among other, DBAs can manage memory usage for In-Memory OLTP workloads using the Resource Governor feature.
We have extensively discussed about In-Memory OLTP in our blog, you can find the relevant articles here.
In addition to the article, you can check our course on Udemy, which can help you to easily get started with In-Memory OLTP in SQL Server.
3. Columnstore Indexes
Another feature that can improve query performance is columnstore indexes.
Columnstore indexes store data in columnar format, allowing for faster retrieval and processing of data. Columnstore indexes can be used by DBAs for large analytical queries that require scanning large amounts of data.
4. Always On Availability Groups
Always On Availability Groups is a high-availability and disaster recovery solution in SQL Server, that provides a collection of synchronized replica databases with the primary database. In the event where the primary database fails, one of the replica databases can take its place.
Always On Availability Groups support up to eight secondary replicas and provide automatic failover.
Example of a SQL Server Always On Availability Groups Architecture
The below diagram illustrates a setup of a 2-node replica with SQL Server Always On Availability Groups.
You can learn more about Always On Availability Groups in this article.
5. Transparent Data Encryption
Transparent Data Transparent Data Encryption (TDE) is a SQL Server feature that encrypts data at rest.
When you enable Transparent Data Encryption for a database, the entire database, including backups, transaction logs, and database files, is encrypted by TDE.
TDE does not require any modifications to the application code or database schema, since the decryption process runs in the background when the database is used. TDE is a very important feature in SQL Server, since it can help DBAs meet security standards and regulations.
You can learn more about Transparent Data Encryption in this article.
6. SQL Server Audit
SQL Server Audit is a feature that provides SQL Server auditing for regulatory/compliance, troubleshooting and performance tuning purposes.
SQL Server Audit has the ability to audit events at the server, database, and object levels. SQL Server Audit can be used by DBAs to track user activity and identify security threats.
For example, among other, by setting up SQL Server Audit (known as audit specifications), you can monitor database activity, such as queries, logins, and schema changes.
Another usage of SQL Server Audit, is for detecting potential security breaches. For example, using SQL Server audits, you can detect and investigate potential security breaches, such as unauthorized access attempts or attempts to modify data.
You can learn more about SQL Server Audit on this link.
7. Stretch Database
Stretch Database, is a feature that was originally shipped with SQL Server 2016, and allows you to move warm and cold data from an on-premises SQL Server database to Azure.
Stretch Database enables you to migrate data to the cloud without having to change your application code or database schema, since it is a process that is transparent to the application.
Stretch Database can be characterized as a low-cost way to store historical data that is accessed infrequently.
You can learn more about stretch database at this link.
In our course on Udemy titled “Introduction to Azure SQL Database for Beginners“, we have included as a special topic, a lecture with a live demonstration of how you can enable Stretch Database in SQL Server. Feel free to check it out!
8. JSON Support
JSON support is another great advanced built-in feature in SQL Server.
Using JSON support in SQL Server, can easily format query results as JSON by just using specific keywords, such as the “FOR JSON” keyword.
This enables you to easily create data processes, that integrate SQL Server with different data services, via the JSON format.
You can learn more about built-in JSON support in SQL Server and Azure SQL Database in this article.
9. Advanced Analytics
Data mining, machine learning, and predictive modelling are all made possible by the advanced analytics features offered by SQL Server.
More precisely, with SQL Server Machine Learning Services, you can integrate advanced analytics and machine learning capabilities directly into your database applications, since among other, you can run R and Python scripts, directly from within SQL Server, with the use of a large number of libraries and tools.
Using these capabilities, you can build and train models that can analyze data that can be found in your SQL Server databases, and produce useful predictions for your business.
You can learn more about SQL Server Machine Learning Services in this link.
10. Temporal Tables
SQL Server Temporal Tables is a feature initially introduced in SQL Server 2016.
Temporal tables enable you to track changes to data in a table over time, thus providing you with unique data auditing capabilities.
To this end, used the functionality offered by temporal tables, you can see how data changes over time, and to query the data as it existed at a specific point in time.
In addition to the above, it is also important to note that the period of validity for every row in temporal tables, is managed by the system (i.e. Database Engine) by using two explicitly-defined columns of the DateTime2 datatype.
You can learn more about temporal tables and see a useful example, in this article.
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Artemakis Artemiou, a distinguished Senior Database and Software Architect, brings over 20 years of expertise to the IT industry. A Certified Database, Cloud, and AI professional, he earned the Microsoft Data Platform MVP title for nine consecutive years (2009-2018). As the founder of SQLNetHub and GnoelixiAI Hub, Artemakis is dedicated to sharing his knowledge and democratizing education on various fields such as: Databases, Cloud, AI, and Software Development. His commitment to simplicity and knowledge sharing defines his impactful presence in the tech community.