STRING_SPLIT() in SQL Server 2016 : Follow-Up #2
Aaron Bertrand rounds out his series on STRING_SPLIT() in SQL Server 2016 with additional tests comparing splitting techniques to TVPs.
2016-06-09
4,804 reads
Articles
2016-06-08
111 reads
Continuous Integration with Microsoft SQL Server
What about database development? In most projects, developers aren’t focused on database development and for proper CI, the database version should keep neck to neck with the application builds.
2016-06-08
4,223 reads
SQL Server AlwaysOn Endpoint Encryption Algorithm Compatibility Error
Ahmad Yaseen takes a look at how to deal with an endpoint encryption compatibility error when using SQL Server's AlwaysOn Availability Group Wizard.
2016-06-08
2,497 reads
Be the first to try Redgate SQL Compare 12
Hot on the heels of the SQL Server 2016 general release, the team at Redgate have just released beta builds for both SQL Compare and SQL Data Compare. As well as support for SQL Server 2016, these releases introduce a brand new user interface, and squash a whole host of bugs. In this blog post, Carly Meichen takes a closer look at what's new, and explains how you can give the development team your feedback and requests.
2016-06-07
7,307 reads
Looking at VIEWs, Close Up
Views in SQL can be difficult. It isn't easy to judge when to use them, It isn't always obvious how to determine if a view can be indexed or if it is updateable. Joe Celko takes a tricky topic and comes up with some helpful guidelines.
2016-06-07
6,986 reads
How to Query Comma Seperated Value Columns in SQL
Karthik provides a simple solution to querying a table that has comma separated values.
2016-06-06
8,568 reads
Using LAST_VALUE
When I began using LAST_VALUE, the results were not what I expected at all. Read on to learn the secret!
2016-06-03 (first published: 2015-04-14)
26,426 reads
The End of Big Data
What is next for big data? Some experts claim that data "volumes, velocity, variety and veracity" will only increase over time, requiring more data storage, faster machines and more sophisticated analysis tools. However, this is short-sighted, and does not take into account how data degrades over time. Analysis of historical data will always be with us, but generation of the most useful analyses will be done with data we already have. To adapt, most organizations must grow and mature their analytical environments. Lockwood Lyon shares the steps they must take to prepare for the transition.
2016-06-03
10,764 reads
Consuming JSON Formatted API Data in 2016
Natively consume JSON data from API sources with SQL 2016 and CLR
2016-06-02
8,889 reads
Blogs
Why your data still can’t answer a simple question
Every organization I talk to has the same problem dressed up in different clothes....
T-SQL Tuesday #197 Invitation – An impactful session or two from a conference
By DataOnWheels
I am delighted to host this month’s T-SQL Tuesday invitation. If you are new...
Did You Really Name That Default?
By alevyinroc
Ten years (and a couple jobs) ago, I wrote about naming default constraints to...
Forums
The day-to-day pressures of a DBA team, and how we can work smarter with automation and AI
Comments posted to this topic are about the item The day-to-day pressures of a...
SQL 2017 to SQL 2025. Good to Go ?
We need to replace our Windows server running SQL 2017. Any reason not to...
Using OPENJSON
Comments posted to this topic are about the item Using OPENJSON
Question of the Day
Using OPENJSON
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