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What are the basic features of a NoSQL database?


NoSQL refers to a database that is non-relational in nature. NoSQL simply means “No use of Structural Query Language,” making it a non-traditional kind of database. Some of the basic features of non-relational databases can be seen below:

Schema flexibility

The data stored in non-relational databases normally has no fixed format. It can exist in free form or a no-schema manner. This entails that a NoSQL database is characterized by flexible schema.

We can see the schema flexibility in the MongoDB code below.

var personalSchema = new Schema({
    name: { type: String, default: 'unknown' },
    age: { type: Number, min: 18, index: true },
    date: { type: Date, default: },

var personalModel = mongoose.model('Person', personalSchema);
var comment1 = new personalModel({
    name: 'Alvan',
    age: '20',
}); (err, comment) {
    if (err) console.log(err);
    else console.log('Preview your entered details as was saved:', comment);

Horizontal scaling

Scaling in a database entails increasing the storage capacity of a database as the application users begin to grow. The increase in the number of users of an application would necessitate an increase in the application’s storage capacity in order to store the data of new users.

This attribute has previously been a difficult one to incorporate into databases. But in NoSQL, horizontal scaling is a possible feature that involves adding additional nodes to the database so as to share the increasing load of storage. This feature is only present in non-relational databases, not in relational databases.

Scaling through additional servers in the MongoDB database

NoSQL data model enables quicker queries

Data is not modeled as fixed tables with fixed rows and columns in a NoSQL database. Instead, it is modeled as graphs with nodes and edges, as well as key-value pairs and other forms. One does not need to determine and declare a table schema before inputting data into a NoSQL database. The flexibility in the data entry format allows for easier data entry in NoSQL databases.

_id: <objectId1>,
 username: "mongoose231",
          phone: "081456893"
          email: ""

access : {
          group: "dev"

The data structure in MongoDB given above permits one to embed document structures in a field within a document. This allows for easy retrieval and manipulation of related data in any given database operation.

Easy use for developers

NoSQL database is characterized by a flexible storage structure. For example, MongoDB is a NoSQL database that uses a document structure in its data storage. One can store both structured and unstructured data in a NoSQL database.

The reason for this flexibility is that most document formats match the object format in most programming languages. This makes it easier for developers to input new data in the database without having to normalize the new data entry with the existing format in the database.

Types of NoSQL database

1. Document database

A document database is a kind of database where a string, path, or URL is used to identify the documents stored in the database. The stored data exists in binary document files in the database. Unique keys are used to pull the selected file documents stored in the database. MongoDB is a good example of a document database, as it permits horizontal scaling in its storage features, which makes it valuable for big data firms.

2. Key-value database

The key-value database is the simplest form of a NoSQL database with very fast performance. Data values are stored in a key-value database with a single key that helps to identify the location as situated in the database. This database type is so simple that it uses simple commands like GET, PUT and DELETE without language complexity. Indexing is not needed to enhance the database performance. Instead, the simple structure of the database makes it fast-performing. Amazon DynamoDB is an example of a key-value database.

3. Wide-column stores

A wide-column database is a kind of NoSQL database that exists as a double-dimensional key-value store. It makes use of tables, rows, and columns to store data in the database. The database columns have a flexible form that could be spread through the nodes of the database. A wide-column database also makes use of multi-dimensional mapping for data referencing by rows, timestamps, and columns. The columns of the database are dynamic in nature. Google Big Table and Microsoft Azure Cosmos DB are two popular examples of wide-column databases.

4. Graph database

In a graph database, data is stored in nodes and edges. The nodes represent information about people, places, and things, while the edges show the relationship existing between the nodes. Graph databases help to store and navigate relationships existing between stored data in a database. Here, we don’t use tables or documents, but nodes and edges. It has a lot of flexibility, as it allows for fast traversing through stored data in a short time. Amazon Neptune is a good example of a graph database.



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