10 Enterprise Use Cases That Are Driving NoSQL Adoption

Personalization is an opportunity to make the right engagement—such as an ad, coupon or recommendation—with the right visitor at the right time. But the ability to ingest, process and use the amount of data necessary to create personalized experiences is a challenge for relational databases. A NoSQL database elastically scales to meet the most demanding data workloads, relies on flexible data models to build and update visitor profiles on the fly, and delivers the low latency required for real-time engagement.

User profile management is core to Web and mobile applications as it enables online transactions, user preferences, user authentication and more. As the number of users, complexity of user profile data and user experience expectations accelerate, relational database technology struggles to keep up with scalability, data flexibility and performance requirements. NoSQL scale-out architecture enables faster, easier and more affordable scalability, provides flexibility to handle changing data types and delivers faster read/write performance.

The ability to extract information from operational data in real time is critical for an agile enterprise—in particular, the ability to increase operational efficiency, reduce costs and increase revenue by acting on current data immediately. Hadoop is engineered for big data analytics, but it’s not real time. NoSQL is engineered for real-time big data, but it’s operational rather than analytical. Using NoSQL together with Hadoop is the answer for real-time big data, Couchbase CEO Wiederhold told eWEEK.

Regardless of industry, every enterprise needs to engage users with rich, informative content. Content isn’t limited to text or neatly structured data. It includes all kinds of semi-structured and unstructured data—images, audio, video and presentations, as well as user-generated content, such as photos, videos, reviews, ratings and comments. Relational databases struggle to manage diverse content types due to their fixed data model. NoSQL databases are able to store rich, complex content with its flexible data model.

Catalogs often contain user-generated content, such as images, reviews, ratings and comments. As enterprises offer more products and services and collect more reference data, catalogs become fragmented by application and business unit or brand. Since relational databases rely on fixed data models, it’s not uncommon for multiple applications to access multiple databases, which introduces complexity and data management issues. NoSQL, with its flexible data model, enables enterprises to more easily aggregate catalog data within a single database.

Creating and maintaining a unified view of customers has been an important but elusive goal for enterprises. Customers expect a consistent experience, while the enterprise wants to capitalize on up-sell/cross-sell opportunities and provide the highest level of customer service. However, as the number of products and services, channels, brands and business units increases, customer data becomes fragmented in silos. The fixed data model of relational databases forces enterprises to fragment customer data because different applications work with different customer data. NoSQL enables multiple applications, not only to access the same customer data, but to add new attributes without affecting other applications.

Mobile phones and tablets are rapidly becoming the dominant platform for search, shopping and other applications. Mobile users spend only 20 percent of their time in browsers and 80 percent within apps. Mobile apps present challenges with scalability, performance and availability that relational databases are not equipped to address. With NoSQL, mobile apps can start with a small deployment and expand as the user base grows, and can be developed faster and launched sooner, which is essential in a market where apps go viral.

Innovative enterprises are leveraging the Internet of things (IoT) to develop new products and services, reduce costs and time to market, increase efficiency, eliminate waste and boost customer satisfaction. This ability to access global, operational data in real-time enables informed decision-making and increases business agility. Relational databases struggle with the volume, velocity and variety of IoT data. Enterprises are using NoSQL to scale concurrent data access to millions of connected devices and systems, store large volumes of data, and meet the performance requirements of mission-critical infrastructure and operations.

We all now rely on digital communications, such as mobile text messaging, online chat and real-time collaboration. However, enabling millions of users to communicate in real time requires both performance and availability at scale, which is a challenge for relational databases. NoSQL databases can easily and elastically scale as more servers are added and deliver sub-millisecond responsiveness that digital communications apps require.

For financial service organizations, fraud detection is essential to reducing profit loss, minimizing financial exposure and complying with regulations. When customers pay with a credit or debit card, they expect immediate confirmation. However, the transaction must be processed by a fraud detection platform, which has to assess customer data and fraud detection rules in less than a millisecond. Relational databases fail to meet this low-latency requirement. NoSQL is able to provide data access at the speed of memory by leveraging an integrated cache.