4 Types of NoSQL Databases & When to use them?

NoSQL databases are popular among developers who are building software or other applications. 

What is the reason? 

Relational databases, with their rigid architecture, are no longer relevant due to their lack of adaptability, scalability, and flexibility. On the other hand, NoSQL databases can handle unstructured and non-structural data and offer scalability, faster development, and superlative performance. 

This blog provides a comprehensive overview of the types of NoSQL databases, their features, advantages, and use cases. 

However, before we delve into the types of NoSQL databases, let’s understand what a NoSQL database is. 

What is a NoSQL Database?

A NoSQL database is a non-relational database. NoSQL simply means “Not Only SQL.” It is a type of database that offers developers a flexible, adaptable, and highly scalable approach to effortlessly store and manage a large set of data volumes. 

Features of NoSQL Databases

No Schema:

A NoSQL Database does not need a pre-defined schema for data storage. It allows businesses not to spend more on expensive data migrations. NoSQL Databases can adapt easily to evolving data structures. 

Scalability

With NoSQL Databases, businesses can distribute data across multiple servers, offering a high level of scalability. 

High Performance

Thanks to their fast read-and-write operations, NoSQL databases are excellent performers. They are perfect for use cases that require real-time data processing and low-latency responses. 

Availability of Data Models

NoSQL Databases offer a wide range of data models, such as graphs, documents, key values, and wide columns. Developers can choose any of these models according to their specific project requirements. 

Support for Big Data

NoSQL Databases can handle a large volume of data, making them the right choice for IoT applications, Big Data analytics, and real-time web applications. 

What Are the Benefits of NoSQL Databases?

Let’s check out some benefits of NoSQL Databases and why developers prefer them over relational databases. 

NoSQL Databases are more flexible, fast, reliable, and perform better than relational databases. 
They are available with flexible schemas, making it possible to adjust the database whenever required. 
Businesses don’t need additional resources to handle large volumes of data, reducing costs by a significant margin. 
NoSQL Databases allow developers to store query-optimized data, making queries faster and easier than SQL databases. 
Some NoSQL Databases like MongoDB map their data structures to those of programming languages, allowing developers to write less code and reduce development time. 

What Are The Types of NoSQL Databases?

Let’s discuss the four types of NoSQL Databases in detail with their use cases. 

Document-Based NoSQL Databases 

As the name suggests, document-based NoSQL Databases store data in documents rather than rows and columns. They use JSON, BSON, or XML documents to store the data. The best thing about document-based NoSQL Databases is that businesses can store or retrieve in a form closest to the data objects used in the application. 

Also, each element has an index value for easy access and faster querying. 

Key Features of Document-Based Databases 

Documents are stored with flexible schemas. 
It is easy to create and maintain documents. 
There is no direct relationship between two documents, eliminating the need to have a foreign key. 
Documents are available in JSON, BSON, and XML formats. 

Use Cases 

Document-based NoSQL Databases are used in content management web applications, product catalogs, user profiles, chat applications, and real-time applications. 

Popular Document-based NoSQL Databases are MongoDB, CouchDB, and Firebase Firestore. 

Key-Value Stores 

This is the simplest form of a NoSQL Database that stores each data element in a pair of keys and values. A unique key is allotted to each data element and is used to retrieve data. The values associated with each data element can be anything from strings to numbers to complex objects. 

Key Features of Key-Value Stores 

Each data element can be accessed through a key, making data retrieval easy and quick. 
It is designed for horizontal scaling and distributed storage. 
Key-value databases are ideal databases for caching and real-time applications.

Use Cases 

Caching, real-time leaderboards, cloud-based scalable applications. 

Popular key-value databases are Redis, Memcached, and Amazon DynamoDB. 

Column-Oriented Databases

Also called “Columnar Databases,” column-based databases are NoSQL Databases that store data in columns, not rows. Businesses can efficiently run analytics on a few columns without looking at unwanted data. These databases are known for their efficiency in reading and retrieving data. Applications that deal with a large volume of data should go for columnar databases. 

Key Features of Columnar Databases 

These NoSQL Databases offer an excellent level of scalability thanks to their support for distributed data processing. 
As data is stored in columns, it offers efficient data compression. 
These NoSQL Databases are perfect for analytical queries, offering superior query performance. 

Use Cases:

Real-time analytics, IoT applications, large-scale Machine Learning models, applications that require distributed storage. 

Popular Column-Oriented Databases are HBase, Apache Cassandra, Google Bigtable. 

Graph-Based Databases

As the name suggests, graph-based NoSQL Databases store data as nodes. Their main focus is to identify the relationships between different data elements. The connections between these nodes are called links or relationships. Here, data is simply represented as nodes and edges, and to retrieve relationships, quick graph traversal algorithms are used. 

Key Features of Graph Databases 

It works on relationship-based storage, making it ideal for recommendation systems and fraud detection systems for social networks. 
Graph databases return query results instantly due to their real-time query processing feature. 
They can be scaled to evolving relationship structures. 

Use cases:

Social networking websites, knowledge graphs, AI recommendations, cybersecurity, fraud detection 

Some of the popular graph-based databases are Neo4j, Amazon Neptune, and ArangoDB. 

Conclusion 

NoSQL databases are fast, flexible, scalable, and offer top-notch performance compared to relational or SQL databases. When businesses have to deal with large volumes of data, going for NoSQL databases is the best solution. They are the perfect choice for modern applications that deal with big data, real-time analytics, AI-powered features, and distributed systems. Choosing the correct type of database for your app development project can help you make data-driven decisions and improve operational efficiency, performance, and scalability.