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Implementing Continuous Integration for Databases

Continuous integration (CI) is becoming more and more common in application development. It ensures code and related resources are integrated regularly and tested by an automated build system, and highlights problems early in the development process. But what about database development? Can the same advantages of CI be applied to production databases? Where do you start? How do you tackle it? Sjors Takes relates his experience.

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How to Create Ten 200GB Test Databases in 60 Seconds

In a recent survey run SQL Server Central, 58% of respondents admitted that their test database is an exact copy of their production database. Many of these respondents concede that they should be removing sensitive data, but aren’t. It seems that the desire to have realistic data will, for many, trump the requirement to keep sensitive data out of development and test environments. In this blog post, Redgate's Jason Crease introduces the new 'SQL Instant Clone' and explains how it could help.

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Question of the Day

The string_agg function

We create the following table and then insert some records in it:

create table t1 (
   id int primary key,
   category char(1) not null,
   product varchar(50)
);

insert into t1 values
(1, 'A', 'Product 1'),
(2, 'A', 'Product 2'),
(3, 'A', 'Product 3'),
(4, 'B', 'Product 4'),
(5, 'B', 'Product 5');
What happens if we execute the following query in both Sql Server and PostgreSQL?
select id, 
category, 
string_agg(product, ';')
                 over (partition by category order by id
                 rows between unbounded preceding and unbounded following) as stragg
from t1;

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