It allows for related data to be stored in one place, rather than distributed across tables. The information is distributed but it is all accessed through one large database management system.Ī document database stores information, most commonly in JSON-like structures, as documents. A user types the address they want to access and the rest is taken care of. However, they are all accessed the same way when searching the internet. Different name servers are owned by different companies. Name servers are used to store these mappings and there are multiple across the globe. However, underneath the hood, these names actually map to unique IP addresses. Internet users everywhere use web addresses, or URLs as they are also known, to access websites and other internet services. The Domain Name System (DNS) uses a distributed database. This tree structure would continue until you reached a level of employee with no direct reports.Ī distributed database is one where the data is related logically but stored in multiple databases across different geographical sites. The CEO could then have many direct reports, such as Chief Technical Officer (CTO), Chief Finance Officer (CFO), and Chief Operating Officer (COO). The root node would be the Chief Executive Officer (CEO) who would have perhaps an ‘EmployeeID’ of 1 and a ‘Level’ value of 0 as they are the root. Organizational ChartĪn organizational chart is a great example of data that can be modeled easily in a hierarchical database. Each ‘parent’ node can have many ‘children.’ The node without a parent is considered the root node. Hierarchical databases represent data in a tree-like form. If a viewer has watched a film starring an actor, they can be shown recommendations of other films that actor has starred in or films directed by someone. This is helpful when building up queries for film suggestions. The edges define the relationships between them, such as a person acting in, directing, or producing a film. The nodes hold information about things such as a person or film. One example of data you can store in a graph database is information about movies and the people who make them. Graph Database ExampleĪ graph database uses nodes to hold data, and edges define relationships between them. To learn more, we have an article about NoSQL database examples. In this section, we'll discuss examples for graph databases, hierarchical databases, distributed databases, and document databases. This means that there are many types of non-relational databases. A patient would also be associated with a doctor via their doctorId, as well as an office they attend for appointments with the officeId attribute.Ī non-relational or NoSQL database is any kind of data store that doesn’t use the traditional tables, column, and rows (sometimes called records) functionality of a traditional relational/SQL database. For example, a column in the 'Doctor' table would store the officeId value from the “Office” table, to represent their office location. The relationship between the tables would be formed from shared columns.

This would mean separate tables for “Doctor” and “Patient.” These tables would have columns such as their unique ID, address, and other relevant information. Entities with one-to-many relationships are typically stored in separate tables. Similarly, there is a one-to-many relationship between offices and patients. This would lead to the creation of an “Office” table, that stores information such as the office's name and address.Īn office could have many doctors, meaning there is a one-to-many relationship between offices and doctors. One common use case for relational databases is storing patient healthcare data.įor example, one healthcare provider might have multiple offices where they see patients.

Columns that are common between tables help form relationships between the data. Relational databases, or SQL databases as they are sometimes called (due to the language that is used to query them), use tables, columns, and rows to store data.

Ninox database examples