Home > Technology > Introduction Whoever said “The only thing that stays constant is change” was wrong. The presence of change may be constant, but change is actually accelerating. Conventional database engines have a very hard time with change. They also have an extremely hard time integrating with each other. The most powerful database engines available today are relational, which are all based on core specifications from the mid-1970s (at a time when requirements were known well in advance, and were not expected to change once systems were designed and deployed). These engines were not designed with the ability to change their table structures on the fly. Traditional software systems that are built using these engines are severely restricted by a bottom-up architecture, meaning that the application and user interface layers are limited by (and entirely dependent upon) the data structure housed within the database. Furthermore, modern coding languages are object-oriented, and have been designed to deal with change. A relational back-end doesn’t match very well with today’s front end tools. The fixed table schema that are used by relational databases are the core bottleneck in the development, lifecycle and flexibility of any data-centric software solution. These fixed schema are the weakest link because they were never intended to change or adapt once activated. In today’s world more than ever before, nothing is more important than the ability to quickly adapt to the changing needs and conditions in the global business environment. The only way to credibly resolve these problems is right at the source — in the database structure itself. If software developers could work with a dynamic data model, that would change the way we manage information itself.