We are currently undergoing a digital transformation that will reshape nearly every aspect of society. The proliferation of smart devices and the rapid integration of artificial intelligence (AI) is changing how industries, companies, and individuals across the globe operate. The foundation of this transformation is data, which enables these innovations and allows institutions to provide better services. The amount of data generated is increasing every year, with the World Economic Forum reporting that 181 zettabytes will be created, captured, copied, and consumed globally in 2025. This is nearly three times as much as in 2020. In order to harvest and use this data, database management systems are becoming increasingly central to the operations of establishments. One database that has become vital in this digital transformation is the NoSQL database.
Why NoSQL Databases Are Essential
As we outlined in our Introduction to Backup and Disaster Recovery, information is now the new oil that drives businesses, organizations, and individuals. NoSQL databases have become essential for these reasons:
Flexible Schema
As technology has evolved, so have the data types that can be collected. 80% of all data harvested today is unstructured data, which is information that doesn’t have a predetermined format or structure, such as audio and video files, images, word documents, social media posts, and code, including JSON and XML. A NoSQL database can easily store and organize this data compared to SQL databases, which store data in tables and columns.
Scalable
One of the defining attributes of NoSQL databases is their ability to scale. Traditional databases will usually scale up vertically by increasing the hardware’s capabilities, such as upgrading the CTU or adding replicas for read-only workloads. A NoSQL database can scale horizontally by adding more nodes to the system to spread the workload, making them ideal for fluctuating workloads such as smart applications or AI models that continuously gather data.
High Performance
NoSQL databases are among the most high-performing databases available due to their low latency and high throughput for data storage and retrieval. Top databases are powerful enough to perform real-time processing and big data analytics and can be used across distributed environments.
Types of NoSQL Databases
There are four types of NoSQL Databases:
Wide Column Store
This database is most similar to an SQL database in that it stores data in tables, rows, and dynamic columns.
What makes it different is its flexibility. MongoDB’s intro to NoSQL databases details how this database employs column compression techniques to reduce storage space and enhance performance. The wide rows and columns can also efficiently retrieve sparse and wide data.
Key-Value
In this database, information is collected and stored as a collection of keys and values. A unique key recognizes each bit of information, and the value accompanying that key can be anything, ranging from string numbers to objects and even other data structures. This is the simplest NoSQL database because it is like a relational database with only two columns – the key and the value – making it fast and ideal for scaling.
Document
The documents in a document database store data in pairs of fields and values. The values can be a wide range of data types, including strings, numbers, booleans, arrays, and other objects. Because there is no dynamic relationship between two documents, each document can be independent of one another, which is why the document database is a very flexible NoSQL database. A key advantage of this database is that it also supports nested structures, making it easy to characterize complex relationships or hierarchical data.
Graph
Graph databases are used to establish relationships between different data points. They store the data in the form of nodes and edges. The node usually contains information about people, places, and things, while edges store information on the relationships between the nodes. To present these relationships, the results are returned in the form of lists, maps, or graph traversal paths.
Use Cases for NoSQL
NoSQL databases are quickly becoming increasingly important in the real world through several use cases:
AI Applications
AI is rapidly changing how we use and communicate with technology. Large language models like ChatGPT are being used in customer support, e-commerce, healthcare, and entertainment through integration with various mobile applications at the forefront of this transformation. Establishments that use these models will likely be using a NoSQL database to store and query the data. A guide by Technology Hits on graph databases explains how they can be used to represent complex relationships between data entities, such as the relationships between words in a sentence, to perform semantic reasoning. This allows AI models like ChatGPT to provide accurate responses.
Streaming Services
Popular streaming services like Netflix use NoSQL databases to store and manage large datasets.
A NoSQL database can store and organize viewing histories, recommendation data, and logs. This information can be stored in different data models depending on the service’s requirements and accessed instantly to provide personalized services. Because streaming services are always growing, the scalability of NoSQL databases allows them to expand seamlessly.
E-commerce Platforms
E-commerce applications must be able to manage a large volume of data, including product catalogs, transaction histories, and customer profiles. By storing this information on a NoSQL database, e-commerce companies are able to provide personalized experiences through product recommendations and personalized offers based on previous purchasing habits. Top e-commerce platforms experience a lot of traffic, which is why they need a high-performing database.
Conclusion
NoSQL databases are becoming increasingly important for storing data and improving services. As technology evolves, more establishments will turn to high-performing databases that can organize and power new innovations.
