Patrick Callaghan

In many ways, the IoT era is already here. But at the same time, we’re nowhere near experiencing the true potential of IoT.

To illustrate, one <a href="https://www.statista.com/statistics/976313/global-iot-market-size/">recent study</a> found that global IoT spend will reach $212 billion this year. Fast-forward to 2025, however, and that number explodes to $1.612 trillion—a roughly 8x increase in six short years.

In the business world, with the proliferation of IoT devices comes a new set of data management challenges. Enterprises need to be able to analyze ever-increasing volumes of data that are arriving rapidly—and conduct that analysis in real time.

IoT data is everywhere. To truly understand the scope, all you need to do is consider one person using a single smartphone. There’s call data, text messages, chats, browsing history, health data, and much more—not to mention the fact that every interaction usually has a time element, which is why time-series data sets are becoming increasingly important. When you think about everyone who has a smartphone—and then you think about things like smart cars, smart sensors, and even smart cities—the totality of the IoT data scale begins to come into focus.

Indeed, IoT interactions are endless. They’re everywhere. Over time, organizations can easily accumulate hundreds of terabytes of data—or even petabytes.

Suffice it to say that legacy systems can’t keep pace with these massive, fast-moving data sets. To thrive in an IoT-powered world, enterprises need a modern approach to data management.

<h2>The 3 kinds of IoT data</h2>

Generally speaking, there are three kinds of IoT data:

<ul>
	<li>Hot data, which is recent data that provides context</li>
	<li>Warm data, which consists of things like summaries and statistics</li>
	<li>Cold data, which is older data that’s used for things like predictive maintenance</li>
</ul>

The latency requirements for each of these types of data vary. For example, while recent data often needs to be retrieved faster, older data usually doesn’t have the same requirements.&nbsp;

That being the case, hot, warm, and cold data all tend to have different SLA requirements.&nbsp;

In addition to these requirements, applications need to be able to scale in a predictable and consistent way. That way, developers can easily add instances to accommodate future and current nodes, no matter what they might be.&nbsp;

Accomplishing all of this requires a powerful, flexible database designed for the modern world. We believe that database is Apache Cassandra™.

<h2>Solving IoT data management challenges with Cassandra</h2>

Most importantly, Cassandra helps manage the hot, warm, and cold data that’s needed to power IoT applications. With built-in data tiering support, you can ensure that hot data is stored in its current state and is the fastest (but most expensive) to retrieve. Further, warm data can be stored in a condensed state (slower to retrieve and cheaper), and cold data can be stored in a data warehouse (even slower to retrieve and cheapest).

But the benefits of Cassandra don’t stop there. Thanks to Cassandra’s masterless architecture, it’s possible to add and sub nodes without having to stop the database. As a result, scaling the database to accommodate increased data volume and throughput becomes an easy process without any downtime.

What’s more, Cassandra was built to be 100% available; there isn’t a single point of failure. Because we’re talking about technology, it’s only a matter of time before something stops working properly. By building an application on top of Cassandra, however, data is automatically replicated across data centers and the cloud—on a global scale, to boot. In the event a node, a rack, a data center, or even an entire region fails, the database itself emerges unscathed.

Due to its versatility, Cassandra can also be deployed in any environment.&nbsp;

Let’s say Azure is the right fit for your application today. But maybe Google Cloud Platform will make more sense in 12 months. With Cassandra, you get the flexibility needed to move your data wherever you want. Otherwise, you’ll just create latency as you move from cloud to cloud.&nbsp;

In the age of rapid application development, <a href="https://www.datastax.com/blog/2019/07/understanding-containers-brief-guide">Docker</a>, and <a href="https://www.datastax.com/blog/2019/07/how-kubernetes-powers-data-management">Kubernetes</a>, this is a big deal.

Add it all up, and Cassandra enables organizations to unlock the full power of IoT data in any environment, ensuring delightful experiences for their users along the way.&nbsp;

For more information on how Cassandra is uniquely positioned to help organizations succeed in an IoT-driven world, check out this webinar: <a href="https://youtu.be/s6cSQN1-PsA">Solving IoT Data Management Challenges with Apache Cassandra</a>.

Solving IoT Data Management Challenges with Apache Cassandra

Patrick Callaghan

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