In the third part of his series on Row Level Security (RLS), Greg Larson shows how to disable RLS for database administrators, sysadmins, and database owners.
2016-06-15
6,385 reads
Paul White discusses the internals of SQL Server's WITH ENCRYPTION clause, and explains why it is not as safe as you might think.
2016-06-14
3,877 reads
The worst part for a DBA of getting started with PowerShell is often just figuring out the best way of working with SQL Server. The most suitable approach to accessing SQL Server depends on the sort of task you need to produce a script for. Laerte Junior aims at a simple guide to the most common approaches and when to use them.
2016-06-14
3,826 reads
Automated configuration management is simpler with Desired State Configuration (DSC) and Push mode, but what is the best way to use DSC to automate deployments on your machines? ‘Push’ mode or ‘Pull’ mode? How can you reduce configuration-drift over time? Nicolas Prigent describes the second DSC deployment mode: Pull mode.
2016-06-13
3,500 reads
There are several decisions to be made when designing indexes for Memory-optimized tables in In-Memory OLTP, and to make the best choice, it pays to understand something about the nature and usage of memory-optimised indexes. Murilo Miranda continues his series by explaining how such an index is unlike a conventional index.
2016-06-10
4,346 reads
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
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
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
Karthik provides a simple solution to querying a table that has comma separated values.
2016-06-06
8,568 reads
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
By Steve Jones
Software is hard. While I love our Lucid Gravity, I realize that they are...
By James Serra
Making Data AI-Ready, Part 2 (This is the second article in a three-part series...
By Steve Jones
Can you use your GPUs when running a local model under Ollama? You can,...
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