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NoSQL Databases: When to Use NoSQL vs SQL

NoSQL databases are widely recognized for their functionality, ease of development, and scalability. They are increasingly used in big data and real-time web applications. In this article, we discuss NoSQL, when to use NoSQL vs SQL, and its use cases — with examples.

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What Is a NoSQL Database?

NoSQL is a type of next-generation database management system (DBMS). NoSQL databases have flexible schemas for building modern applications with large amounts of data and high loads.

The term “NoSQL” was first coined by Carlo Strozzi in 1998, although similar databases have existed since the late 1960s. However, development of NoSQL began in earnest in early 2009 and it is growing rapidly.

The response time of any relational database management system (RDBMS) can become slow when dealing with massive amounts of data. To resolve this, we can “scale up” information systems by upgrading existing hardware, which is very expensive. However, NoSQL scales out better and is more cost-effective.

NoSQL is extremely useful for unstructured or very large data objects such as chat log data, video, or images. That is why NoSQL became particularly popular with internet giants like Microsoft, Google, Amazon, Meta (Facebook), etc.

Some popular NoSQL databases include:

  • MongoDB
  • Amazon DynamoDB
  • Apache Cassandra
  • Apache CouchDB
  • Apache HBase
  • RavenDB
  • Elasticsearch
  • Redis
  • OrientDB
  • Neo4j
  • Cosmos DB
  • HyperTable

Read more: What Is a Relational Database? Your Complete Guide

When to Use NoSQL vs SQL

As businesses accumulate larger datasets more rapidly, structured data and relational schemas do not always fit. It becomes necessary to use unstructured data and large-scale objects to better capture this information.

Traditional RDBMS use SQL (structured query language) syntax to store and retrieve only structured data. Conversely, NoSQL databases encompass a wide range of functionalities that can store and retrieve structured, semi-structured, unstructured, and polymorphic data.

Sometimes, NoSQL is also called “Not Only SQL,” emphasizing that it may support SQL-like languages or sit alongside SQL databases. One differentiator between SQL and NoSQL DBMSs is JOIN functionality. SQL databases use JOIN clauses to combine rows from two or more tables. Because NoSQL databases are not inherently tabular, this functionality is not always feasible or relevant.

However, some NoSQL DBMSs can perform operations similar to JOIN — as is the case with MongoDB. This doesn’t mean that SQL DBMSs are no longer needed; rather, NoSQL and SQL databases tend to solve similar problems in different ways.

In general, NoSQL is preferable to SQL when:

  • The organization works with a huge amount of data
  • The data is not strongly related
  • The data is not structured
  • The database needs to consistently scale

Read more: Structured Data vs Unstructured Data: Differences & Examples

NoSQL Use Cases

Many industries are adopting NoSQL, replacing relational databases to give some business applications higher flexibility and scalability. Some enterprise use cases of NoSQL databases are given below.

Content Management (CM)

Content management is a set of processes for the collection, managing, delivery, retrieval, and publishing of information in any format including text, images, audio, and video. NoSQL databases can offer a better option for storing multimedia content with their flexible and open-ended data model.

For example, Forbes built a custom content management system based on MongoDB in just a few months, giving them greater agility at a lower cost.

Real-Time Big Data Processing

Big data refers to a dataset that is too large to be handled through traditional processing systems. Systems that store and retrieve big data in real time use stream processing to ingest new data while analyzing historical data, a series of functions that are ideally suited to NoSQL databases.

Zoom used DynamoDB (on-demand mode) to enable its data to scale without performance issues, even as the service saw usage spike in the early days of the COVID-19 pandemic.

Read more: Using Zero Trust Security to Protect Applications and Databases

Internet of Things (IoT)

IoT devices have embedded software and sensors that are connected to the internet or communications networks, and are able to collect and share data without human intervention. With billions of devices generating untold amounts of data, IoT NoSQL databases provide scalability and more flexible schema to IoT service providers.

One such service is Freshub, which switched to MongoDB from MySQL to better deal with its large, dynamic, non-uniform datasets.

Mobile Applications

With billions of smartphone users, scalability is becoming the biggest challenge for businesses that deliver services on mobile devices. A NoSQL DBMS, with more flexible data models, is often the perfect solution.

For instance, The Weather Channel uses a MongoDB database for handling millions of requests per minute while also processing user data and delivering weather updates.

NoSQL Databases Solve Modern Problems

Data management has become one of the most important issues facing businesses today. NoSQL databases are designed to

Read next: What Is Serverless Architecture?

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