Semi-structured data
Semi-structured data does not follow the typical row–column table format or conform to a rigid schema structure; therefore, it cannot fit completely in the relational databases category. However, it is not entirely unstructured either. Semi-structured data is somewhere in between these two categories and is characterized by the following features:
- Schema flexibility: It is adaptable to changes and accepts structure in the form of hierarchical data format and keys.
- Nestedness and hierarchy: Semi-structured data often has a hierarchical or a nested structure and its data elements are often grouped within other elements, forming a tree-like structure. This results in representations such as eXtensible Markup Language (XML) or JavaScript Object Notation (JSON).
- Without a fixed datatype: Semi-structured data can have elements of varying data types within the same dataset. For example, a JSON document can contain strings, Booleans, numbers, and...
