Query store and in-memory oltp – simple talk

In-Memory OLTP is an advanced feature of SQL Server that you can use to gain incredible performance in high transnational workloads. Database in recovery With the release of Service pack 1 for SQL Server 2016 this previously Enterprise-only feature became available on all edition of SQL Server 2016. Data recovery wizard professional So how does the Query Store interact with In-Memory OLTP? As it turns out, both technologies play nicely with each other, though some special attention is required if you want to get the most out of both of them. Data recovery open source What is In-Memory OLTP?

In-Memory OLTP, codename ‘Hekaton’, is a technology aimed at making the execution of transactions and access to data more efficient.


Gif database Although it was first introduced in SQL Server 2014 as an Enterprise-Only feature, it then became available on all editions of SQL Server 2016 with the release of Service pack 1.

In-Memory OLTP introduces memory-optimized tables, meaning that they reside entirely in the memory of your server but are fully durable. Data recovery lifehacker By ‘durable’, we mean that a restart, or crash, of SQL Server that forces your memory to flush doesn’t impact the Memory-optimized table. Top 10 data recovery software 2014 Along with introducing Memory-optimized tables, Microsoft completely changed the lock and latch behavior for those queries that accessed Memory-optimized tables, removing the contention that can occur on traditional disk-based tables.

Another very powerful addition to the In-Memory OLTP technology is the natively compiled stored procedure. Database gale Natively compiled stored procedures are similar to traditional stored procedures but they are directly compiled into native (machine) code. Database life cycle This means that natively compiled stored procedures avoid the interpretation that is required for normal stored procedures and can run directly on the CPU. Data recovery dallas Natively compiled stored procedures are restricted to execution against Memory-optimized tables, but are very efficient in use.

So let’s take a look how the Query Store interacts with queries against Memory-optimized tables and the usage of natively compiled stored procedures! Setting up out tests

Before we can get started with analyzing Query Store data in combination with In-Memory OLTP, we have to configure our test database. Data recovery usb For this I am going to use the AdventureWorks database on my test system. Database 4th normal form This database has the Query Store enabled. V database in oracle If you want to replay these tests yourself, make sure it is enabled before running the demos.

The first thing we need to do before a database can use In-Memory OLTP is to create a Memory-Optimized Filegroup to our database. Data recovery tampa The queries below will add a filegroup called “InMemory” to the AdventureWorks database and create a file that holds our durable Memory-Optimized table data.

There they are! After enabling the collection of statistics for our test natively compiled stored procedure the runtime statistics are saved inside the Query Store! Keep in mind though, just like regular queries against Memory-Optimized tables, IO and memory statistics are not captured when running natively compiled stored procedures. R studio data recovery with crack And don’t forget that enabling the collection of statistics for natively compiled stored procedures can negatively impact their performance. Database uses Summary

When you have the Query Store enabled on databases that use In-Memory OLTP features like Memory-Optimized tables and natively compiled stored procedures, query and plan information is captured automatically. Database history For normal queries runtime statistics are also automatically captured but when you are using natively compiled stored procedures we have to explicitly enable the collection of runtime statistics. Database b tree Not everything is captured for either queries that run against Memory-Optimized tables or for natively compiled stored procedures. Database optimization Runtime statistics regarding IO and memory consumption will remain in the runtime statistics DMVs and Query Store reports.

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