In this book, Kalen Delaney explains how the 2016 In-Memory OLTP engine works, how it stores and manipulates data, and how, even with all data stored in memory and no locking or latching, it can still guarantee the ACID properties of all transactions.
If you don't have a good reason not to, use a relational database. Always.
Although it is easy to use SQL Server R Services to create R scripts that incorporate SQL Server data by passing in a T-SQL query as an argument when calling the sp_execute_external_script stored procedure, you are limited to that one query, unless you pass additional data directly between R and SQL Server via CSV files. It is simple to do, and opens up many additional opportunities for data analysis. Robert Sheldon explains how.
Power BI provides correlation plot visualization in the Power BI Visuals Gallery to create Correlation Plots for correlation analysis. In this post, Siddharth Mehta shows how to create a correlation plot in Power BI Desktop using a sample dataset of car performance.
Brent Ozar explains why DBAs should read this book about the future of database administration at scale.
A bug in American Airlines scheduling could impact travelers, but certainly will impact their bottom line.
After many barren years, Phil Factor is pleased to see the first signs of Spring in SSMS.
To support many applications, it makes sense for the database to work with JSON data, because it is the built-in way for a JavaScript or TypeScript application to represent object data. It can mean less network traffic, looser coupling, and less need for the application developer to require full access to the base tables of the database. However, it means that the database must do plenty of checks first before importing. Phil Factor explains how it can be easily done.
SQL Server works well, and Microsoft does everything it can to keep it relevant and competitive: As with everything in real life, it doesn't don't always get it completely right, and Rob Sheldon continues his quest through the jungle of past features to rediscover and explore the ones that time forgot. Here, he comes across Lightweight Pooling, XML Indexes, Stretch Databases, SQL Variants, Transaction Savepoints and In-Memory OLTP.
By Vinay Thakur
In previous posts, we looked at the SQL Server engine. for us DBAs, the...
By Arun Sirpal
You have used Claude. But which Claude? The Claude app (claude.ai, the desktop and...
By Steve Jones
This month we have a new host, Meagan Longoria, who graciously agreed to help...
Comments posted to this topic are about the item Creating a JSON Document IV
By VishnuGupthanSQLPowershellDBA
Comments posted to this topic are about the item Restoring Azure Key Vault Keys...
When the schema of an object is changed, SQL Server wipes out the previous...
I have this data in a table called dbo.NFLTeams
TeamID TeamName City YearEstablished ------ -------- ---- --------------- 1 Cowboys Dallas 1960 2 Eagles Philadelphia 1933 3 Packers Green Bay 1919 4 Chiefs Kansas City 1960 5 49ers San Francisco 1946 6 Broncos Denver 1960 7 Seahawks Seattle 1976 8 Patriots New England 1960If I run this code, how many rows are returned?
SELECT YearEstablished, json_objectagg(city : TeamName) FROM dbo.NFLTeams GROUP BY YearEstablished;See possible answers