MongoDB
MongoDB is a document database that stores data as key-value pairs in JSON documents. Each document can hold various types of data, including arrays, Booleans, numbers, strings, and nested documents. By using Binary JSON (BSON), MongoDB holds additional data types and processes data efficiently. With the data storage flexibility in MongoDB, you can store unstructured, evolving, and dynamic data.
MongoDB organizes each document into collections, with each having a unique ObjectId, which you use to identify a document. The following table shows an example of customer data in MongoDB.
customers:[
{
customer_id: “1”,
name: “John Doe”,
country: “United States”
},
{
customer_id: “2”,
age: “35”
email: “jane_doe@example.com”
}]
PostgreSQL
In contrast, PostgreSQL is an object-relational database management system (ORDBMS) that combines object-oriented features with relational database capabilities. In a table, every row represents individual data points, and each column defines the type of information that you store there. PostgreSQL supports a range of data types, including dates, text, integers, and Booleans.
Unlike MongoDB, PostgreSQL uses a predefined schema to store data. A schema allows for strong data consistency and integrity, as each column holds a specific data type. However, it’s less flexible. We share an example in the following table.
dbo.customers
customer_id
name
age
1
John Doe
24
john_doe@example.com
2
Jane Doe
35
jane_doe@example.com