Since I first blogged about NoSQL back in 2013, the use of “Not Only SQL” databases for mission-critical applications has proliferated across businesses of all sizes and sectors. With trends like big data analytics, cloud, mobile and IoT driving the modern digital enterprise, requirements for greater application performance and scalability combined with falling storage costs increasingly bias the playing field toward non-relational databases.

Is relational database (RDBMS) technology still the “reigning data champion”? Yes, but the gap has closed significantly. NoSQL’s more flexible data storage formats are helping to solve a range of problems that traditional relational databases struggle to address. 

What are the top NoSQL use cases these days? Here are five of the most prevalent:

1. Real-time/Near Real-time Big Data Processing

The faster a company can process and act on fresh data, the greater its operational efficiency and business agility, and the greater the bottom-line value of its data. A typical approach to real-time big data processing uses stream processing to ingest new data combined with Apache Hadoop for analyzing historical data, plus a NoSQL database that integrates with both. 

Payments processing leader PayPal is a prime example of a leading digital enterprise that processes big data on-the-fly and leverages it in multiple ways. PayPal captures vast quantities of raw clickstream data—more than 20 TB per day!—in multiple formats by processing it through Hadoop and Apache HBase NoSQL databases, and storing it all in the cloud for worldwide access by business analysts and data scientists. Fraud detection, data mining, customer segmentation and delivering personalized ads to customers are just some of the differentiating capabilities that PayPal has built on NoSQL.

2. Internet of Things

As of 2021, it’s estimated that about 46 billion IoT devices, from smartphones to home appliances to healthcare systems to factory sensors to smart vehicles, are now connected to the Internet. The amount of semi-structured data these devices continuously generate adds up to something like 847 zettabytes

NoSQL databases are better suited than their relational counterparts to scale out to ingest this endless fire hose of diverse data. Freshub, a smart kitchen web platform for food shopping, is one example among many of an application that successfully processes data from huge numbers of IP-connected appliances. The Freshub solution maintains a MongoDB NoSQL cloud database of over 1 million grocery products gleaned from online catalogs in real-time. In this use case, NoSQL is well suited to integrate diverse and unpredictable data schemas from all these sources. NoSQL also scales out horizontally across an arbitrary number of cloud database nodes as Freshub grows its customer and data footprint.

3. Content Management

Online shopping now surpasses brick-and-mortar sales, and “content is king” across thousands of online marketplaces and web storefronts. Online sales leaders curate a selection of multimedia content (including user-generated and social media content like reviews, photos and videos) and deliver it to shoppers “at the moment of interaction.” 

NoSQL document databases offer a flexible, open-ended data model that is ideal for storing a mix of structured, semi-structured and/or unstructured content. NoSQL also makes it possible to aggregate data that serves multiple business applications within a single catalog database. Whereas RDBMS with its fixed data models tend to result in the proliferation of multiple, overlapping catalogs for different purposes.  

Forbes.com, which lives on viewership and ad revenue, exemplifies the use of NoSQL technology for content management. Forbes quickly built a custom content management system based on MongoDB in just a few months, giving them greater agility—including the ability to incorporate contributor content and analyze social sharing within clickstream data—at a lower cost. The same data store also feeds their mobile site, which now gets 50% of their total traffic.

4. Mobile Apps With Huge Numbers Of Users

Mobile phone and tablet use recently surpassed desktops as the top online platform for searching, shopping and otherwise viewing web content. Interestingly, as much of 90% of mobile data is served via apps and only 10% through browsers, an overwhelming shift in recent years.

Rapidly scaling mobile apps globally to serve tens of millions of users with acceptable performance (think mobile gaming or popular social media apps) often calls for distributed databases, which in turn calls for NoSQL. Flexible NoSQL data models also support rapid app update cycles better than relational data models in many cases. 

For these reasons, more and more businesses looking to monetize web content are using NoSQL data stores for their apps. A popular case in point is The Weather Channel, whose MongoDB database instance handles millions of requests per minute while also processing user data and juggling weather updates from tens of thousands of worldwide locations.

5. Enriching The Digital Customer Experience

An engaging differentiating digital customer experience is built on data-intensive, time-critical capabilities like personalization, user profile management and a unified view of the customer across all your touch points. A lot of this demographic, behavioral and logistical data comes from the online clickstream, creating a write-intensive, multi-schema workload that taxes “scale-up” RDBMS infrastructure. A distributed NoSQL database can scale more cost-effectively, manage an ever-growing number of attributes with less administrative hassle, and often delivers lower latency—the Holy Grail of online interactions where you’re trying to get ads, recommendations, coupons, etc. in front of users in real-time.  

Multimedia service provider Comcast uses a Couchbase NoSQL platform to deliver a positive customer support experience across multiple lines of business. A core goal of the platform is to capture data from huge numbers of omnichannel interactions (phone calls, online help, chatbots, etc.) and relate it all back to individual customers’ accounts and service status. Scalability and resilience are also critical concerns, as in any customer experience scenario. Especially because the better your solution works, the more customers will use it.

Other NoSQL Use Cases & Conclusion

  • Real-time updates and queries
  • Discussion thread hierarchy
  • Data caching and archiving
  • Simple data collection and analysis functions associated with voting and surveys
  • Cross over data analysis that cannot be conducted in relational environments
  • Online gaming where numerous simple queries need to run in fractions of a second

As these current NoSQL use cases illustrate, the strengths that I highlighted back in 2013, like flexible data models, low latency, ease of delivery/maintenance and the ability to integrate structured, semi-structured and unstructured elements, continue to make NoSQL a preferred choice for “digital transformation” across industries. The ongoing success of NoSQL innovators and early adopters like Netflix, Amazon, Twitter, Facebook and AOL continues to pave the way for new solutions.

Wondering if NoSQL technology is right for your application, how to architect a new NoSQL solution or how to move your current RDBMS to a NoSQL alternative? Contact Buda Consulting for a 15-minute “database discussion” to explore whether we can help. 

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