“Complex query intensive environments.”
I would imagine anything that needed to track a large amount of data points, that could then be searched through. Time tracking temperature for example.
“Hierarchical data storage”
I think lab 11 would qualify, there are descriptions and titles and availability.
NoSQL
They are both scalable, just depends on which one it is. SQL is vertically scalable and you can increase the load by adding CPU, RAM, SSD etc onto a single server. NoSQL is also scalable, but horizontally, and you can increase it by adding more servers.
Structured Query Language
A relational database is a type of database that stores and provides access to data points that are related to one another. Relational databases are based on the relational model, an intuitive, straightforward way of representing data in tables. In a relational database, each row in the table is a record with a unique ID called the key. The columns of the table hold attributes of the data, and each record usually has a value for each attribute, making it easy to establish the relationships among data points. https://www.oracle.com/database/what-is-a-relational-database/
Tables
A database schema defines how data is organized within a relational database; this is inclusive of logical constraints such as, table names, fields, data types, and the relationships between these entities. Schemas commonly use visual representations to communicate the architecture of the database, becoming the foundation for an organization’s data management discipline. https://www.ibm.com/topics/database-schema
A database that is built to store lots of data in an efficent way.
Within the database there are collections, within those collections they have documents. Relations are not necessary and not all information is needed. They are more flexible than SQL.
See the first sentence to the last answer.
MongoDB, see below.
No schemas, no relations, data is usually nested.