Unstructured Data vs Semi-Structured Data

A document database grows by defining tables and fields, similar to a relational database.

Semi-structured data lacks the structure of formal database architecture but can have associated metadata.

Unstructured data is typically harder to create than structured data.

Key/value pair tables require all properties to be defined for each object.

Key/value pair databases predetermine the fields used to define an object.

Documents in a key/value pair database commonly use XML for structuring.

JSON stands for JavaScript Object Notation.

Semi-structured data includes raw data without any additional information like metadata.

Non-relational databases like document databases do not have formal structures to link different data objects.

NoSQL databases can stand for 'Not Only SQL'.

Structured Query Language (SQL) is critical in relational database management systems (RDBMS).

Key/value pair tables always need the same properties defined in the same order for each object.

In a file-based storage model, when one user opens the file, it becomes locked to other users.

Relational databases organize information in tables known as relations.

A relational database uses NoSQL to maintain and query data in the database.

Semi-structured databases have a fixed schema for data organization.

Databases provide access controls to ensure data is disclosed to unauthorized users.

Scalability in databases refers to the ability to expand usage without cost implications.