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

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.

Companies often grow through mergers and acquisitions, and as they expand inorganically, the issues and challenges faced by them are numerous. The major issues are synergy evaluation, technology integration, selecting the management team, resolving cultural issues, and internal and external communications.

One pattern that shows up repeatedly is creating a Many-to-Many relationship using a mapping class. In Rails, the hasMany/through directive provides this functionality. Grails doesn't have an explicit hasMany/through statement like Rails. Rather, Many-to-Many relationships are created implicitly by GORM via your domain classes.

As mobile developers, our applications will need to both aesthetically display the results of our data queries, as well as give users an intuitive interface to store and insert data. In this article by Jason Wei, author of Android Database Programming, we will focus on the former – on binding data to the user interface (UI) and will look specifically at various classes that will allow us to bind our data in the form of lists (the most common and intuitive way to display rows of data).

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.

Part 1 of this two-part article covers the basics of achieving a consistent, concise domain model and persistence tier with modern object-relational mapping (ORM) tools. In Part 2, the authors describe base domain entities, behavior in the domain model, and more-advanced features of a generic DAO. They also share strategies for enhancing data-retrieval performance with the domain model.

Relational databases define a strict structure and provide a rigid way to maintain data for a software application. Apache's open source CouchDB offers a new method of storing data, in what is referred to as a schema-free document-oriented database model. Instead of the highly structured data storage of a relational model, CouchDB stores data in a semi-structured fashion, using a JavaScript-based view model for generating structured aggregation and report results from these semi-structured documents. CouchDB has been developed from the ground up with Web applications as the primary focus and has its sights on becoming the de-facto database for Web application development.

The objective of this paper is to present the Whitemarsh approach to the definition of function points within database-centric business information systems, the process of counting function points, and the use of two metrics derived from function point counts to accomplish business information system estimating.

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.