Database administrators are used to dealing with query performance issues. As part of this duty, it is an important aspect to identify the query and troubleshoot the reason for its performance degradation. Normally, we used to enable SET STATISTICS IO and SET STATISTICS TIME before executing any query.
SQL Server 2017 introduced Graph database features where we can represent the complex relationship or hierarchical data. We can explore the following articles to get familiar with the concept of the Graph database.Read more »
Data compression is required to reduce database storage size as well as improving performance for the existing data. SQL Server 2008 introduced Data compression as an enterprise version feature. Further to this, SQL Server 2016 SP1 and above supports data compression using the standard edition as well.Read more »
SQL Server 2019 has a rich set of enhancements and new features. In particular, there are many new feature improvements in the database engine for better performance and query tuning.Read more »
SQL Server was launched in 1993 on WinNT and it completed its 25-year anniversary recently. SQL Server has come a long way since its first release. At the same time, Microsoft announced a preview version of SQL Server 2019. SQL Server 2019 provides the ability to extend its support to big data, Apache Spark, Hadoop distributed file system (HDFS) and provides enhancements to database performance, security, new features, and enhancements to SQL Server on Linux.Read more »
This article is part 4 of the series for SQL Server 2019 Enhanced PolyBase. Let quickly recap the previous articles.Read more »
In this article on PolyBase, we will explore more use case scenarios for external tables using T-SQL.Read more »
SQL Server 2019 offers powerful new features to help in safeguarding your data and complying with various privacy regulations, which we’ll be covering in this articleRead more »
In this article, we’ll take a look into SQL truncate improvement in SQL Server 2019.
Data inserts and updates are a normal and regular task for the developers and database administrators as well as from the application. The source of the data can be in multiple forms as if direct insert using T-SQL, stored procedures, functions, data import from flat files, SSIS packages etc.Read more »
In the previous article of the series, we took an overview of PolyBase in SQL Server 2017. We also learned about the Azure Data Studio and SQL Server 2019 preview extension to explore SQL Server 2019 features.Read more »
Microsoft released preview of SQL Server 2019 recently in Ignite 2018. With every release of SQL Server is enriched with new dynamic management view and functions along with enhancements to existing features.
In this article, we will view the newly introduced dynamic management function (DMF) sys.dm_db_page_info and explore the different scenarios around it.Read more »
On September 24th, 2018, Microsoft launched SQL Server 2019 preview version (SQL Server vNext 2.0) in the ignite 2018 event. As you know, SQL Server 2017 is still being adopted by the organizations, we are now ready with this preview version.Read more »
Monitoring databases for optimal query performance, creating and maintaining required indexes, and dropping rarely-used, unused or expensive indexes is a common database administration task. As administrators, we’ve all wished, at some point, that these tasks were simpler to handle.Read more »
SQL Server 2017 is considered a major release in the history of the SQL Server life cycle for various reasons. From my personal point of view, SQL Server 2017 is indeed an interesting release. After writing lot about it and testing various features of SQL Server 2017, I’d like to walk you through some of its interesting features.Read more »
In this 18th article of the series, we will discuss the concepts of database backup-and-restore of SQL Server Docker containers using Azure Data Studio. Before proceeding, you need to have Docker engine installed and Azure Data Studio configured on your host machine.
This article covers the following topics:
- Overview of Azure Data Studio (ADS)
- How to use Azure Data Studio integrated terminal
- Definition of Docker containers
- Step by step instructions to initiate backup-and-restore of SQL Server 2017 Docker containers using the Azure Data Studio interface
- And more…
I’ve always been in favor of an orthodox strategy when it comes to applying SQL Server updates which often goes like:
- Instead of installing SQL Server Cumulative Updates, wait for release of service packs
- When a service pack is released, install it in phases starting from the non-production environment (i.e. DEV, UAT) to eventually roll it out on production
The new SQL Server 2017 comes with new features in the installation. It now supports Machine Learning Services that support R and Python. It also includes SSIS Scale Out Master and Scale Out Worker. It also includes scale out options in PolyBase.Read more »
So far, we’ve discussed several phases of backup that starts with planning, creating, strategizing and implementing. In this article, we are going to see how database administrators can define the strategy to improve backup performance and efficiently manage backups in SQL Server 2017. The following are the topics of discussion:
- Discuss checkpoints
- Discuss the enhancements made in the Dynamic Management View (DMV) sys.dm_db_file_space_usage for smart differential backups
- Discuss the enhancements made for the Dynamic Management function (DMF) sys.dm_db_log_stats for smart transactional log backup
- Understand the functioning of smart differential backup and its internals
- Understand the Smart transaction log backup process and its internals
- T-SQL scripts
- And more…
SQL Server 2017 brings a new query processing methods that are designed to mitigate cardinality estimation errors in query plans and adapt plan execution based on the execution results. This innovation is called Adaptive Query Processing and consist of the three features:
- Adaptive Memory Grant Feedback;
- Interleaved Execution;
- Adaptive Joins.
SQL Server chooses parallel plans based on the costing (there are also some other factors that should be met for the plan that it can go parallel). Sometimes serial plan is slightly cheaper than a parallel, so it is assumed to be faster and picked by the optimizer, however, because the costing model is just a model it is not always true (for a number of reasons, enlisted in Paul’s article below) and parallel plan runs much faster.Read more »
While preparing the post about Adaptive Joins, I’d like to share a quick post about the hidden gem in SQL Server 2017 CTP 2.0, discovered recently. In this short post, we will look at how you can determine what statistics are used by the optimizer during a plan compilation in SQL Server 2017.
Prior to SQL Server 2017, there were two ways how you could do it, both undocumented and involving undocumented trace flags.Read more »
This article explores SQL Sort, Spill, Memory and Adaptive Memory Grant Feedback mechanism in SQL Server.Read more »
In this post, we are going to look at the new feature in SQL Server 2017 – interleaved execution. You need to install SQL Server 2017 CTP 1.3 to try it, if you are ready, let’s start.
Now, when a CTP 2.0 of SQL Server 2017 is out, you don’t need to turn on the undocumented TF described further, and the plans are also different, so the examples from this post use CTP.1.3, probably not actual at the moment (I was asked to hold this post, until the public CTP 2 is out, and interleaved execution is officially announced). However, the post demonstrates Interleaved execution details and might be still interesting.Read more »
Nowadays a lot of developers use Object-Relational Mapping (ORM) frameworks. ORM is a programming technique that maps data from an object-oriented to a relational format, i.e. it allows a developer to abstract from a relational database (SQL Server, for example), use object-oriented language (C#, for example) and let an ORM to do all the “talks” to a database engine by generating query texts automatically. ORMs are not perfect, especially if they are used in a wrong way. Sometimes they generate inefficient queries, e.g. a query with redundant expressions. SQL Server has a mechanism to struggle with that inefficiency called a query simplification.Read more »