There is no such thing as NoSQL. Not as we tend to think of it, anyway. While NoSQL was born as a movement away from rigid relational data models so web giants could embrace Big Data with scale-out architectures, the term has come to categorize a set of databases that are more different than they are the same.

This broad categorization doesn’t work. It’s not helpful.

While we at MongoDB still sometimes refer to NoSQL, we try to do it sparingly, given its propensity to confuse rather than enlighten.

Deconstructing NoSQL

Today the NoSQL category includes a cacophony of over 100 document, key-value, wide-column and graph databases. Each of these database types comes with its own strengths and limits. Each differs markedly from the others, with disparate models and capabilities relative to data storage, querying, consistency, scalability and high availability.

Comparing a document database to a key-value store, for example, is like comparing a smartphone to a beeper. A beeper is exceptionally useful for getting a simple message from Point A to Point B. It’s fast. It’s reliable. But it’s nowhere near as functional as a smartphone, which can quickly and reliably transmit messages, but can also do so much more.

Both are useful, but the smartphone fits a far broader range of applications than the more limited beeper.

As such, organizations searching for a database to tackle Gartner’s three V’s of Big Data -- volume, velocity and variety -- won’t find an immediate answer in “NoSQL.” Instead, they need to probe deeper for a modern database that can handle all of their Big Data application requirements.

Modern Databases For Modern Data

One of these requirements is, of course, the ability to handle large volumes of data, the original impetus behind the NoSQL movement. But the ability to handle volume, or scale, is something all databases categorized as “NoSQL” share. MongoDB, for example, counts among its users those who regularly store petabytes of data, perform over 1,000,000 operations per second and clusters that exceed 1,000 nodes.

A modern database, however, must do more than scale. Scalability is table stakes. It also must enable agility to accelerate development and time to market. It must allow organizations to iterate as they embrace new business requirements.

And a modern database must, above all, enable enterprises to take advantage of rapidly growing data variety. Indeed the “greatest challenge and opportunity” for enterprises, as Forrester notes, is managing a “variety of data sources,” including data types and sources that may not even exist today.

In general, all so-called NoSQL databases are much more helpful than relational databases at storing a wide variety of data types and sources, including mobile device, geospatial, social and sensor data. But the hallmark of a modern database its ability to allow organizations to do useful things with their data.

Defining The Modern Database

To count as a modern database, then, a database must meet three requirements. While relational databases are able to manage some of these requirements, and newer so-called “NoSQL” key-value or wide column data stores meet others, only MongoDB meets all three requirements.

• The database MUST scale. As data volume and velocity grows, so the database must grow too. It should scale horizontally and elegantly, without doing unnatural things to your application, in the cloud or on commodity hardware. Meeting the base requirements -- like having enough capacity to serve your customers -- should be a given.
• The database MUST adapt to change. The speed of business accelerates and your database must keep pace, enabling iteration. This means you must be able to process and mine new data sources and data types without the database breaking a sweat (or you breaking your back or budget). Your schema must flow from your application requirements, rather than forcing your application to fit a predefined, rigid schema.
• The database MUST unleash your data. Just storing data isn’t enough. You must be able to exploit the data, which particularly means you must be able to ask significant questions of your data. In part this means that the database must support rich queries, indexing, aggregation and search across multi-structured, rapidly changing data sets in real time. But it also means that it must support data for modern use cases including mobile, social, Internet of Things and other systems of engagement.

Some relational databases can handle a few of these requirements, yet fail in the essential need to deliver scale and adaptability. Some newer databases, including so-called “NoSQL” key-value or wide column data stores, meet still other requirements, yet don’t give organizations the latitude to unleash their data. In fact, they constrain you to look up data by the key with which it was written unless you integrate external search engines and analytics nodes, which can create other problems.

MongoDB: A Modern Database For Today's Business Needs

But only one database today can deliver on each of these critical components of a modern database. Only one database offers orders of magnitude more productivity for developers and operations teams alike, while still delivering petabyte scale and lightning-fast performance.

Only MongoDB, the modern database that tens of thousands of organizations depend upon to build and run today’s most demanding applications.

To learn more about how MongoDB has enabled some of the world’s largest and most innovative companies to deliver applications and outcomes that were previously impossible, download our new whitepaper.