Relational Databases

D.

The database type that should be used with highly structured data and provides support for ACID (Atomicity, Consistency, Isolation, Durability) transactions is the relational database.

Relational databases organize data into tables with rows and columns, and establish relationships between the tables through keys. They are well suited for structured data with clearly defined relationships and constraints, such as financial data, inventory management, and customer relationship management. Relational databases are designed to ensure data integrity, consistency, and accuracy through the use of ACID transactions, which are essential for many business-critical applications.

ACID transactions guarantee that database transactions are executed reliably and consistently, even in the event of a system failure or interruption. Atomicity ensures that transactions are treated as a single unit of work, where either all of the changes are committed or none of them are. Consistency ensures that data remains in a valid state throughout the transaction, regardless of how many changes are made. Isolation ensures that multiple transactions can be executed concurrently without interfering with each other. Durability ensures that changes made to the database are permanent and can be recovered in the event of a system failure.

On the other hand, time series databases are used to store and manage time-series data, such as sensor data, financial data, and IoT data, and are optimized for time-based queries. Document databases are designed to store and manage semi-structured data, such as JSON and XML documents. Graph databases are used to store and manage graph-like data structures, such as social network data and recommendation engines. While these databases have their unique strengths, they do not provide the same level of support for ACID transactions as relational databases do.