Relational vs. Non-Relational Databases

No. Relational, or SQL databases, store data in tables with common columns between them (known as primary and foreign keys), forming relationships between tables. The data is always structured with a defined schema that cannot easily be changed.

But there are other database types, under the non-relational/NoSQL database title, that hold unstructured, semi-structured, or structured data. These allow for flexibility and high availability. Some examples are MongoDB, Cassandra, and CouchDB.

Yes. MongoDB is a document database, a type of non-relational database. Data is stored in collections as BSON documents, which are JSON-like in structure. The data is considered unstructured because a collection can contain documents with different fields and data types, allowing for high flexibility.

Non-relational databases are great for a wide range of use cases due to their flexibility and scalability (both horizontally and vertically).

For example, a key-value database would be a great fit for storing settings in an app, as each setting will have only one value. For an e-commerce site, a document database would be ideal, as you can store a document for each client, which will have their details and order history stored together, as they are private and unique to each client.

A graph database is a great solution for fraud detection, where the relationship between data is vital but the types of data are often unpredictable.

Relational databases store data in a tabular format as rows and columns. The relationships between data are defined using multiple tables. For example, to determine the relationship between customer and their orders, we need two or more tables: the customer table and order table. Non-relational databases don’t follow a rigid structure and are suitable for storing huge amounts of data of different types in a single view. Read more on relational vs non-relational databases.

There are many use cases for a non-relational database. For example, they are suitable for obtaining real-time data for operational and analytical purposes. Because of the nature of big data, non-relational databases are also a good choice for AI applications and IoT-based applications that need superior performance and horizontal scaling.

A popular example of document-type non-relational databases is MongoDB, which stores data in a JSON-like format. This format makes it easier to traverse the data and view all the data in a single view. MongoDB also has rich query capabilities and aggregation functions that make data retrieval and analytics easy and faster.

Relational databases are more suitable for data that’s not likely to change frequently. You can use relational databases for medium to large datasets.

Non-relational databases can be used for real-time data and faster query results. Because of their flexible schema, they can also easily store huge amounts of unstructured data.

Some popular examples of relational databases are MySQL, SQLServer, PostgreSQL, and Oracle.