Converting Trace to Extended Events
A walkthrough of a conversion of a SQL Trace setup to an Extended Event session.
A walkthrough of a conversion of a SQL Trace setup to an Extended Event session.
In-Memory OLTP (project “Hekaton”) is a new database engine component, fully integrated into SQL Server. It is optimized for OLTP workloads accessing memory resident data. In-Memory OLTP allows OLTP workloads to achieve significant improvements in performance, and reduction in processing time. Tables can be declared as ‘memory optimized’ to enable In-Memory OLTP’s capabilities. Memory-optimized tables are fully transactional and can be accessed using Transact-SQL. Transact-SQL stored procedures can be compiled to machine code for further performance improvements on memory-optimized tables. The engine is designed for high concurrency and blocking is minimal.
One of the teams at Red Gate is releasing new changes every Wednesday, which reminds Steve Jones of a time earlier in his career.
Today we have a guest editorial from Andy Warren that asks what you might do when you get settled at a new job.
Every DBA needs to appropriately manage database growth. No DBA wants an application to fail because the database is out of space. A database can run out of space a number of different ways. One of those ways is to set the MAXSIZE of a database. When the database grows to the MAXSIZE the database will not grow anymore and if someone tries to add more rows they will get an error saying the database is full.
Will there be a fair balance between the coming generations of technology and the human workforce? Here is a list of industries that may not think yes.
One of the greatest things that has arisen in the past 10 years or so is a veritable stream of great conferences for people to learn how to write better software, many of them low cost or even free. In the Data Platform community, we have had nearly 800 free SQL Saturday events around the […]
Steve Jones talks a bit about the difference between state based and migrations based approaches for deployment.
By HeyMo0sh
Working in DevOps, I’ve seen FinOps do amazing things for cloud cost control, but...
Every organization I talk to has the same problem dressed up in different clothes....
By DataOnWheels
I am delighted to host this month’s T-SQL Tuesday invitation. If you are new...
Comments posted to this topic are about the item The day-to-day pressures of a...
Hello all, I’m looking for advice on how to derive a daily snapshot table...
We need to replace our Windows server running SQL 2017. Any reason not to...
I have some data in a table that looks like this:
BeerID BeerName brewer beerdescription 1 Becks Interbrew Beck's is a German-style pilsner beer 2 Fat Tire New Belgium Toasty malt, gentle sweetness, flash of fresh hop bitterness. 3 Mac n Jacks Mac & Jack's Brewery This beer erupts with a floral, hoppy taste 4 Alaskan Amber Alaskan Brewing Alaskan Brewing Amber Ale is an "alt" style beer 8 Kirin Kirin Brewing Kirin Ichiban is a Lager-type beerIf I run this, what is returned?
select t1.[key]
from openjson((select t.* FROM Beer AS t for json path)) t1 See possible answers