NoSQL use cases are rising as developers build apps that generate massive data and require scalable, flexible, performance for semi/unstructured data.
With the rise of big data, IoT data, AI, and machine learning, demand for NoSQL databases is projected to grow at a 30% CAGR (compound annual growth rate) from 2024 to 2030.
Advanced technologies generate massive amounts of data and require real-time analytics—demands NoSQL databases are built to handle.
Unlike traditional relational databases, which struggle to keep up with many modern applications, NoSQL databases, like Astra DB, are scalable, flexible, cost-effective workhorses. They give developers the power to manage and store diverse data that’s structured, semi-structured, or unstructured.
Let’s look at the benefits across industries:
Then, we’ll see how the increasingly popular NoSQL DB powers international corporate juggernauts in the real world:
Built on Apache Cassandra® - a massively scalable open source database loved by AI leaders - Astra DB powers responsive, consistently - accurate AI applications without artificial hallucinations.
You can use a NoSQL database for any high-throughput application, but there are a few common use cases where NoSQL shines:
E-commerce platforms store and access large data sets like product catalogs, customer profiles, and transaction histories. NoSQL databases are capable of handling high traffic volumes, making them an excellent choice for e-commerce content management systems that experience surges in demand.
Semi-structured data and unstructured data are challenging to manage with traditional relational databases. But NoSQL databases provide the necessary scalability and performance to support high-traffic e-commerce applications.
In e-commerce, a NoSQL database stores product data, including product descriptions, prices, images, and availability, making it easy for customers to search for and find the products they need.
NoSQL databases store customer profiles, including names, addresses, purchase histories, and preferences, allowing e-commerce companies to build personalized experiences for their customers, via targeted product recommendations and personalized offers.
Transaction histories provide a complete record of all transactions that have occurred in the e-commerce application, which is meaningful data for reporting.
Social media platforms generate vast amounts of unstructured data in the form of
This data is highly variable and unpredictable, making it difficult to manage with traditional relational databases. NoSQL databases, on the other hand, are designed to handle unstructured data and provide the necessary scalability and flexibility to support social media applications.
One of the main advantages of NoSQL databases here is their ability to store, process, and retrieve unstructured data at scale, quickly and efficiently.
Astra DB:
The only vector database for building real-world, production-level AI applications using real-time data.
The Internet of Things (IoT) is a network of connected devices that generate vast amounts of data from sensors, cameras, and other sources. IoT is used in
This large data is often unstructured or semi-structured, making it difficult to manage with traditional relational databases. NoSQL databases, however, are designed to handle the high-volume variety of data from IoT devices that’s generated continuously. And they offer the flexibility to accommodate evolving data models.
With NoSQL databases, IoT applications collect and analyze data from millions of devices in real-time, providing valuable insights into user behavior, performance, and maintenance needs.
NoSQL databases are also highly scalable, which is essential for IoT applications that may need to accommodate tens of thousands or even millions of devices. As the number of devices and the volume of data grows, NoSQL DBs horizontally scale to accommodate the additional load. This scalability is critical for IoT applications that need to process large amounts of data quickly and efficiently. To learn more about IoT architecture, data model, and queries, check out this dedicated IoT use case page.
Billions of users worldwide generate vast amounts of data using mobile applications, including user profiles, location data, and app usage statistics. NoSQL databases provide fast, reliable access to data across a distributed network.
The advantage of NoSQL databases for web and mobile applications is their ability to handle semi-structured and unstructured data like
This flexibility is critical for mobile applications that need to store and process data in a variety of formats almost instantly.
From player data to game states to high scores, NoSQL databases are an excellent choice for gaming companies because they store and manage large volumes of player data—and variable demand surges—with ease.
Gaming companies must maintain a vast amount of player data, including profiles, preferences, progress, and achievements. NoSQL databases can handle this data effectively, allowing gaming companies to access and analyze player data efficiently.
To learn more about gaming architecture and how Astra DB can power leading gaming apps like ESL gaming, visit our gaming use case page.
Relational databases struggle with similarity tasks, which are crucial for many AI applications.
Big data analytics has become a crucial tool for companies to gain insights from their operational data, customers, and markets. Traditional relational databases are often not well-suited for big data analytics because they struggle to handle large volumes of unstructured data.
NoSQL databases are an excellent choice for big data analytics that manage
NoSQL databases can handle it all, providing fast and flexible access.
NoSQL databases scale horizontally, allowing companies to add more computing power and storage as needed. This scalability means that NoSQL databases can handle even the largest data sets with flexible data models essential for big data analytics.
In traditional relational databases, data must be organized into a rigid structure, which can be limiting when dealing with unstructured data. NoSQL databases, on the other hand, can handle a variety of data models, including
This flexibility gives companies a way to store data and analyze data how it best suits their needs.
Let's explore some real-world examples of companies that use NoSQL databases and the applications for which they use them.
Netflix uses NoSQL databases to store and manage
With a NoSQL database, Netflix provides fast, reliable access to data across a distributed network.
Uber uses NoSQL databases to handle the massive amounts of data generated by its ride-sharing platform, including
NoSQL databases provide the scalability and flexibility needed to handle high traffic volumes and changing data models.
Airbnb uses NoSQL databases to store and manage data for its booking platform, including
Airbnb handles large volumes of unstructured data and, thanks to its NoSQL database, renters take advantage of fast, reliable access to data across a distributed network.
SQL databases remain popular because they have had a much longer market presence and work well for structured applications.
NoSQL databases are growing in popularity because modern applications increasingly use unstructured data. Developers need real-time processing that is flexible and scales. Big data demands that.
When choosing which database works best for an application, look to NoSQL when you need these benefits for specific use cases:
NoSQL databases are designed to scale horizontally, so companies can more easily add more computing power (nodes) and storage as needed. This makes NoSQL databases an excellent choice where developers build large-volume applications to handle traffic spikes—without sacrificing high performance.
NoSQL databases offer flexible data models that can accommodate evolving data needs. This means that companies can easily add or modify data fields without having to restructure their entire database schema.
NoSQL databases offer high availability and fault tolerance, ensuring that applications remain up and running even in the event of a hardware failure or network outage. This is critical for applications that require continuous availability, such as e-commerce and social media platforms.
NoSQL databases are optimized for fast read and write speeds, making them an excellent choice for applications that require real-time data access, such as mobile applications and gaming platforms.
DataStax drives the generative AI revolution, empowering companies to deliver AI-powered applications that redefine business.
Astra DB is a fully-managed NoSQL database service. It’s the industry’s only vector database for building real-world, production-level AI applications using real-time data.
What else?
It is fast, scalable, and highly available, giving developers the ability to easily create and manage their database without having to worry about the operational overhead that comes with a traditional SQL database.
Plus, it’s run by developers who obsess over other developers and enterprises. DataStax works hard to help developers build powerful, accurate Generative AI applications in a fraction of the time, at a fraction of the cost, with the scale and performance they need. DataStax Astra DB makes all data, including vectors, instantly available. And with the freedom to operate on any cloud, building in the language of your choice, we’re making AI accessible to millions of developers building the AI-powered applications of the future.
Here are some of the benefits of using Astra DB for your NoSQL use cases:
Astra DB is a fully-managed service, which means that developers focus on building applications instead of managing database infrastructure.
Astra DB exists so developers can focus on writing code. In the background, Astra DB is a workhorse for
Astra DB has a simple user interface that makes it easy to create and manage databases. Developers can also use Astra DB's REST API and SDKs to integrate their applications with Astra DB.
Astra DB is highly available and scalable, with built-in replication and automatic scaling. This ensures that applications remain up and running even in the event of a hardware failure or traffic spike. It’s everything you expect in a NoSQL database, plus it’s built and supported by developers for developers. DataStax’s mission is to serve production-level AI applications with a vector database fueled by real-time, real-life customer and streaming data.
DataStax is at the forefront of the generative AI revolution, with proven technologies that empower any organization to deliver AI-powered applications that redefine business.
DataStax's Astra DB is the industry’s only vector database for building real-world, production-level AI applications using real-time data.
Built on Apache Cassandra®—the massively scalable open source database proven by AI leaders—Astra DB is the data engine for responsive AI applications that consistently deliver accurate results, without artificial hallucinations.
Thousands of developers and hundreds of the world’s leading enterprises, including Audi, Capital One, The Home Depot, VerSe Innovation, rely on DataStax technologies.
A NoSQL database manages a massive amount of data and is built to accommodate traffic growth. These databases are well suited to handle hundreds of millions of complex queries. They allow for horizontal scalability, deliver a consistent experience at high velocity, and are great for accessing and storing semi-structured and unstructured data at the high-performance level that modern developers expect.
Some of the biggest companies in the world use a NoSQL database to achieve operational efficiency and business agility. Netflix manages its customers profiles, viewing histories, live streaming, and content recommendations with NoSQL, and uses it to process and share scalable data across distributed networks.
NoSQL database systems are preferred for data-intensive applications such as agile development. AstraDB is an example of a NoSQL database.