What is the most common method for storing structured data?

The most common method for storing structured data is through relational databases. Structured data is highly organized, typically follows a predefined schema, and is easily categorized within tables and rows, making relational databases an ideal storage solution.

Relational databases use Structured Query Language (SQL) to define and manipulate the data, which allows for efficient querying and data management. The data integrity and relationships between different data points are maintained through the use of primary and foreign keys, ensuring that data remains consistent and accurate.

In contrast, a data mart is a subset of a data warehouse, specifically designed for a particular department or business line, and may not always focus on structured data alone. A data lake, on the other hand, is designed for storing vast amounts of raw data in its native format, which can include both structured and unstructured data; this makes it less suitable for situations where structured data management and querying are priorities. NoSQL databases, while excellent for handling large volumes of unstructured or semi-structured data with high flexibility, are not the standard choice for structured data compared to relational databases.