Agile methodologies work well with database developments only if great care is taken to do things right. It requires good judgement and leaves little room for error. Dev Nambi, in an extract from the book Tribal SQL, argues that Agile works for smart, curious, and experienced software engineers.

The job of a DBA requires a fusion of skill and knowledge. To acquire this requires a craftsman mindset. Craftsmen find that the better they get at the work, the more enjoyable the work gets, and the more successful they become. Deliberate practice, Specialization and an appetite for overcoming difficulty are good habits to deliberately adopt to successfully grow those craftsmanlike skills to the point that you become “so good they can’t ignore you”.

Learn how to set up and use the universal database connection technique known as Open Database Connectivity in conjunction with the web development language PHP. This is an introductory article for the technologies required to make an open, reliable, and standardized web application — namely, PHP, ODBC, and SQL.

Conflicting requirements, such as those related to security, performance, and economy, multiply the challenge of integration developments typical in programming in the oil-and-gas industry. One technique that can help ease the burden on slimmed-down development teams is to centralize database accesses through the open source SQL Relay product.

Often, an existing database application must evolve rapidly by incremental steps. Alex describes a tried and tested system to provide an automated approach to deploying both new and existing database systems, whilst dealing with common security and configuration issues.

draws a comparison between two approaches to ORM-centric database development. One is based on the Python SQLAlchemy ORM tools, and the other uses standard Java JPA. Which is better? The result of comparing a simple use case for both languages is quite surprising.

There aren't many frameworks for writing acceptance tests for databases, including SQL Server. FitNesse is an obvious choice since it is designed with a Wiki-style interface that, once it is configured and set up correctly, makes it very easy for a non-specialist to set up individual tests.

This article covers some basic techniques to optimize the performance when working with an ORM and still getting all the benefits of Object-Relational mapping

The increasing use of XML asks for systems that store semi-structured data without forcing it into inadequate data structures. These requirements are met by both native XML databases and relational databases with integrated XML support. The question is: Why should you prefer a native XML database over an XML-aware classic database or the other way around? This article compares the approaches of a number of varying solutions, including eXist, Mark Logic, and IBM DB2 Express-C. The differences are translated into practical advantages and disadvantages.

This article focuses on another area that Grails makes easy: persistence using the Grails Object Relational Mapping (GORM) API. I'll start by describing what an object-relational mapper (ORM) is and how to create a one-to-many relationship. Next, you'll learn about data validation, ensuring that your application isn't plagued with garbage in/garbage out syndrome. You'll see the Grails ORM domain-specific language (DSL) in action, which allows you to fine-tune how your POGOs (plain old Groovy objects) are persisted behind the scenes. Finally, you'll see how easy it is to swap out one relational database for another. Any database with a JDBC driver and a Hibernate dialect is fair game.