DataStax

As we move further into the IoT era, millions of new devices are coming online every hour.&nbsp;

This uptick in gadgets results in a tsunami of data that’s capable of drowning unprepared organizations across all industries. Staying above water requires having the proper tools in place to handle the proverbially massive waves.

Originally, IoT devices required cloud-based compute and storage capabilities. However, with the rise of <a href="https://www.datastax.com/blog/2019/07/four-cloud-technology-trends-watch-out">edge computing</a>, which allows you to run workloads wherever you want, and AI, which essentially needs to run everywhere, organizations are increasingly realizing that it’s impossible to unlock the full potential of these leading-edge technologies without the right underlying infrastructure.

Good news: Companies like Microsoft and DataStax are innovating in this space to ensure that customers are able to maximize their investments in IoT-powered technologies.

<h2>Maximizing IoT Investments with Azure and DataStax</h2>

On one hand, Azure IoT solutions can help companies keep pace with the increasing scale and speed required for telemetry data.&nbsp;

On the other, databases like open source <a href="https://www.datastax.com/resources/definitions/what-is-apache-cassandra">Apache Cassandra™</a> and <a href="https://www.datastax.com/products/datastax-enterprise">DataStax Enterprise</a> (DSE)—which is built on top of Cassandra—can serve as the underlying storage layer that ties it all together.

Both databases are fully distributed. Built with <a href="https://www.datastax.com/resources/infographic/3-reasons-you-need-masterless-architecture">masterless architecture</a>, Cassandra and DSE can operate at unlimited scale, are continuously available, and have no single point of failure.&nbsp;

Traditionally, the databases have been used to build highly available scalable applications—which makes them the perfect fit for the IoT era.

For example, using Cassandra Query Language (CQL)—which is very similar to SQL—you can select specific sensor readings, time ranges, limits, and more to optimize your IoT investments and support time series data requirements.&nbsp;

What’s more, Cassandra and DSE can also <a href="https://docs.datastax.com/en/opscenter/6.5/opsc/LCM/configTieredStorage.html">accommodate</a> hot data (e.g., recent data that provides context for analysis purposes), warm data (e.g., data that’s used to automated algorithms and things like predictive maintenance), and cold data (e.g., data that might only need to be consulted every now and again)—much-needed functionality for IoT use cases.&nbsp;

Do you really need to know right this second what a sensor measured 273 days ago?

At the same time, due to their built-in support for scale, the databases can process upwards of 1M events that occur every second.&nbsp;

But that’s just the beginning.

To learn more about how Microsoft and DataStax solutions can help your organization realize the full promise of the IoT frontier, check out this <a href="https://www.datastax.com/resources/webinar/iot-solutions-delivering-speed-and-scale">on-demand webinar</a> hosted by Patrick Callaghan, VP of enablement at DataStax, and Ridhi Jhavar, principal solution specialist for the IoT device experience team at Microsoft. 
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