| | *Relational databases (e.g. MySQL) are probably the most common. Essentially they store data in a set of 2D tables (relations) that follow certain rules of normalization and can be linked to each other via relational algebra (mostly set theory type functions). | | *Relational databases (e.g. MySQL) are probably the most common. Essentially they store data in a set of 2D tables (relations) that follow certain rules of normalization and can be linked to each other via relational algebra (mostly set theory type functions). |
| | *To address problems encountered when trying to interface a RDBMS with an object-oriented programming language, alternative non-relational database structures (e.g. XML, NoSQL, Hierarchical, Network) are available and may have advantages in certain situations. | | *To address problems encountered when trying to interface a RDBMS with an object-oriented programming language, alternative non-relational database structures (e.g. XML, NoSQL, Hierarchical, Network) are available and may have advantages in certain situations. |
| | Each primary key (disease) can be associated with multiple values in each attribute. For example, CAD is associated with multiple risk factors (age, male gender, smoking, etc) and multiple symptoms (angina, dyspnea, nausea, etc). At the same time, each of these risk factors and symptoms are associated with other diseases besides CAD. For example, smoking is a risk factor for CAD, lung cancer, PVD, COPD, head and neck cancer, etc. In order to handle this many-to-many cardinality of the data, multiple base tables should be created and an associative table (junction table) can then be created as needed. The base tables in the above example would be: | | Each primary key (disease) can be associated with multiple values in each attribute. For example, CAD is associated with multiple risk factors (age, male gender, smoking, etc) and multiple symptoms (angina, dyspnea, nausea, etc). At the same time, each of these risk factors and symptoms are associated with other diseases besides CAD. For example, smoking is a risk factor for CAD, lung cancer, PVD, COPD, head and neck cancer, etc. In order to handle this many-to-many cardinality of the data, multiple base tables should be created and an associative table (junction table) can then be created as needed. The base tables in the above example would be: |