Why and When to Use a NoSQL Database: 6 Use Cases

While Structured Query Language (SQL) has been the standard model for databases since the 1980s, NoSQL (Not only SQL) databases have been gaining in popularity in recent years. The rise of big data and cloud computing has created a need for a different type of database—one that is scalable, flexible, and able to accommodate a range of data types, including unstructured data. In fact, for certain types of data and applications, NoSQL is the preferred option. This article will discuss what NoSQL is and the use cases where NoSQL is preferable over SQL.

What is a NoSQL database?

First, what is NoSQL? Since NoSQL stands for “Not Only SQL,” NoSQL databases can handle data beyond the typical relational database. So much of today’s data is unstructured, and can include documents, graphs, and key-value pairs in addition to tables. Unstructured data does not fit neatly into a SQL table-based database schema. NoSQL databases provide high performance, scalability, and flexible schemas.

These traits are well-suited for modern applications, such as social media, chat, Internet of Things (IoT), and gaming applications. NoSQL has evolved so that there are many options to choose from, depending on your database and application needs. A few of the most popular NoSQL databases include MongoDB, Redis, and Apache Cassandra.

Types of NoSQL data models

NoSQL databases use a variety of data models. The four main types of NoSQL databases are key-value, document, column-oriented, and graph databases.

• A key-value database stores data as key-value pairs. Data can be accessed quickly in this format. Redis is a popular example of a key-value NoSQL database.
• The document database is good at storing semi-structured or unstructured data, usually in the form of JSON or XML. MongoDB is the most well-known document database.
• The column-oriented database stores data in columns instead of rows, making querying faster. This type of database is good for big data and complex querying. Apache Cassandra is a column-oriented database.
• The last type of NoSQL database is a graph database. Graph databases are good at querying interconnected data, such as figuring out preferences based on past purchases. Neo4j is an example of a graph database.

When to use SQL vs. NoSQL

NoSQL was born out of necessity, since SQL databases had limitations on the type of data that was permissible. If your data did not fit into a traditional tabular format, it was difficult to shoehorn the data into an SQL schema. If your data queries require complex joins, your application could become very slow. SQL databases are difficult and expensive to scale as your data grows. Some agile developers found that they were limited by the constraints of traditional SQL technology. They couldn’t add new features without major updates to the database schema, which involved a costly data engineering effort.

Keep in mind that there are still scenarios where it is best to use an SQL database. If your data is well structured and fits into a fixed schema, SQL is best. These types of applications include financial systems, customer relationship management (CRM) systems, and enterprise resource planning (ERP) systems. SQL has a large development and support community and a wide selection of mature tools. But if your data does not fit neatly into SQL, consider NoSQL.

Why should you use NoSQL?

The following are a few of the reasons why NoSQL is becoming a more popular database option, and in some cases preferable to SQL.

• Scalability: NoSQL databases are highly horizontally scalable, as they are designed to distribute data across multiple servers. SQL databases can be expensive and, in some cases, impossible to scale. Instead of investing in more expensive hardware to scale up as you would have to do with SQL databases, you can take advantage of NoSQL’s “scale-out” architecture, spreading the storage and processing power among a large cluster of computers.
• High performance: You need high performance with limited to no downtime. NoSQL databases deliver high performance for read and write operations. Unlike SQL databases, NoSQL databases do not use complex joins, which slows down response times. NoSQL databases can handle massive volumes of user-generated content and real-time updates.
• Cost-effectiveness: NoSQL is cost effective because of its horizontal scalability. As data increases, you can easily add another server to distribute the data. NoSQL requires less database management than SQL, thereby lowering your costs. In addition, many NoSQL databases are open source.
• Easy updates: NoSQL databases store data in an easy-to-understand format, such as JSON, XML, or key-value stores. In addition, NoSQL databases are not built on a set schema, so it’s easy to add a new data type without redesigning the database schema.

What is NoSQL good for? 6 Use cases

The following use cases demonstrate where you may be better off using a NoSQL approach to your data.

1. Handling massive datasets

   If you know your data will keep growing and growing, you may want the scalability of NoSQL. Instead of investing in costly vertical scaling with a high-powered server, you can scale horizontally. Social media platforms are an example of massive datasets that require scalability. NoSQL can handle storing content like user-generated posts, likes, friends, and followers on a large scale.

2. Managing unstructured or semi-structured data

   If your data is always changing and does not fit into a predefined schema, NoSQL may benefit you. In addition, you may be dealing with semi-structured and unstructured data such as JSON, XML, or video content. Content management systems (CMS) such as WordPress are an example of storing semi-structured and unstructured data, such as blog posts and media files.

3. Enabling agile development practices

   NoSQL databases work well with agile development practices, since they do not need to adhere to a strict database schema. Developers can prototype and test new features quickly without worrying about redesigning the database. They can continue to develop and improve with each subsequent sprint. For example, streaming services like Netflix benefit from using NoSQL in its agile development. NoSQL provides flexible schema design, scalability, and decentralized data management. These factors allow for the rapid development and deployment of new features.

4. Demanding high-performance workloads

   Certain applications demand high performance, such as e-commerce platforms. Any downtime for your application means a decrease in sales. You want the customers to see updated information about pricing and inventory in real time. When your data needs grow, you want to be able to add a server without incurring downtime. Amazon uses its own NoSQL offering, DynamoDB, to handle many aspects of its e-commerce operations.

5. Modeling complex relationships

   NoSQL can model complex relationships that go beyond what a SQL database can do. NoSQL can represent relationships, such as parent-child and many-to-many relationships, without relying on slow join operations between tables. Social media applications are a good example of complex relationships because they store relationships among users such as friends and friends-of-friends.

6. Monitoring data in real time

   Certain applications, such as IoT applications, involve ingesting large volumes of data generated by devices and sensors. The application must provide immediate insights and further actions to take. NoSQL can handle complex, unstructured IoT data, such as logs and time-series data, so the application can detect patterns and discover anomalies.

Connect to your NoSQL database with CData

CData Connect Cloud is an ideal cloud-based solution for integrating with NoSQL databases like MongoDB and Redis, among others. Connect Cloud allows you to connect directly to your live NoSQL data from the client tools you use every day, without installing additional software. You can manage all your connections in real time from a central interface. Simply supply your authorization credentials and you will be up and running quickly.