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Driving Data with an ORM

Published 1 year ago

Many of today's most useful applications derive their usefulness from a relational database. By collecting and storing information in a well-designed collection of tables, we can create powerful and efficient e-commerce, social, scientific, and all sorts of other platforms.

Of course, interfacing with such databases can be tricky. Most RDBMS (relational database management systems) use SQL, or Structured Query Language, to manipulate data. While application platforms can certainly use SQL directly to store and retrieve information, the simple truth is that such a process often produces poor results. Code ends up duplicated, costing time and money, and introducing opportunities for bugs. It may leverage specific behavior for a given DB, thus making potential migrations more difficult. Further, that deep integration requires developers to be more familiar with the database in order to do their job – and while better-educated developers aren't bad, it can increase the learning curve, which again strains budgets.

Fortunately, there is a better way.

Given the obvious problems with a direct approach, a number of frameworks have sprung up to bridge the gap between code and database. These frameworks are called ORMs – object-relational mappings – and they are available for pretty much every language in use today. They encapsulate all the specifics of managing the database, and marshal the information in and out of your application in a simple and direct fashion. By leveraging an ORM framework, applications can be developed much more quickly and with fewer bugs.

It's important to note that ORMs are not a silver bullet. As in any situation where another framework is introduced, there may be reduced performance or limited flexibility. Naturally, there are constant improvements to most actively-used libraries, but situations may still exist that require bare-metal access to get the job done. In such cases, it may be worth a “mix and match” approach – using the ORM to insert data, perhaps, but handling reporting and analysis through direct queries (if not separate tools entirely).

It's also important to consider that there are a number of different ORM libraries available for any given language. While there are certainly front-runners – Hibernate for Java, Entity Framework for .NET, Doctrine for PHP, Sequelize for node.js, and so on. There are many options that may work more or less effectively and efficiently for a given use case.

Whatever the language, whatever the database, and whatever the framework: if you've got a data-driven application, an ORM may be worth investigating. The teams at Smart Software are well-versed in a number of frameworks across many languages and can help you determine what's right for your project.

AUTHOR Bryce Mayrose

Bryce Mayrose is a graduate of the University of South Dakota, and has worked for Smart Software Solutions since August 2006. During that time, he has participated in a range of projects utilizing a wide array of technologies. He particularly enjoys programming data-driven applications with C# and SQL Server -- but PHP and MySQL are a bit of a guilty pleasure, too. When not busy in front of a computer, he likes to spend quality time with his wife Ronda and their four sons, his Kindle, or a good video game.