You identified a query that is causing performance issues, and your mission is to optimize it and boost performance. You looked at the execution plan and created all the relevant indexes. You even updated statistics, but performance is still bad. Now what?
In this session we will analyze common use cases of poorly performing queries, such as improper use of scalar functions, inaccurate statistics and the impact of parameter sniffing. We will learn through extensive demos how to troubleshoot these use cases and how to boost performance using advanced but practical techniques. By the end of this session, you'll have many powerful techniques to apply to solving query performance issues.
Today's applications are not using monolithic approach anymore and evolving into micro-services architecture. Monitoring tools are also evolving, micro-services approach have stepped into this area as well.
What you should do if you have several technologies under your responsibility? SQL Server and MySQL? Maybe Hadoop or PostgreSql? Should you use separated tool for each product? Should you use the same tool for Monitorig and Alerts, incidents management and notifications?
There are many cloud SAAS products in addition to traditional on-premise monitoring products and in this session, we will talk about their advantages and disadvantages.
The incredible Columnstore Indexes can increase your analytical query processing speed multiple times, they are updatable (Clustered from SQL Server 2014 and Nonclustered from SQL Server 2016 respectively), but they keep on supporting different sets of the functionalities – such as Change Data Capture (Nonclustered Columnstore) or LOBs (Clustered Columnstore), and this brings a great confusion onto the table.
This session will light up your path on when to use what functionality to use and when, even though sometimes one of the type of the Columnstore Indexes does not seems to appear as a default choice for your scenario.