The data usage patterns have changed dramatically in the last ten years or so, and various organizations are interested in 'hidden' relationships between data - ones that were not initially recognized or planned for the database. This is when the graph databases may be used.
When you approach a new project, you are often tasked with the design of the data structures that will support the application. The data structures should allow for the required functionality and they should follow some principles of data modeling, like normalization, proper data types, etc.
How do you approach such tasks? Thinking in categories of tables is not always the best approach. Tables look like business entities, but not always. How do you model relationships between tables?
The article focuses on these two database technologies, but they can be extended to the whole realm of RDBMS and NoSQL databases.
Certain aspects of both domains can be considered as advantages or disadvantages, depending on the point of view and particular business case. The flexibility of schema in MongoDB is appealing to teams who implement applications dealing with unstructured data. The strictness of schema definition required by relational databases can be beneficial when the application needs to ensure that the data quality meets certain requirements.
Shopping Cart
Your cart is currently empty.
Enable cookies to use the shopping cart