Manage any type of IoT Data with always on, distributed and scalable modern database.

Break data silos and boundaries and unlock the full potential of IoT data.

icon

Telemetry Data Management at Global Scale

Solve any challenges related to collecting and managing IoT telemetry data with a highly available, resilient and scalable modern distributed database that allows you to collect and store mission-critical data close to the edge, in any cloud and on-premises.

icon

IoT Data Management

A decentralized IoT hub allows you to manage, administer and ingest data at speed and velocity from IoT devices globally with high efficiency and low latency and with full flexibility of deployment options in hybrid clouds and at any cloud provider.

icon

Get the Most from Your IoT Data

Scalable, always on and distributed by design, DataStax Enterprise Analytics and Enterprise Search are the perfect pair to apply data science tools to your IoT Data and unlock the full potential of your data.

IoT Solution Architectures

Explore how DataStax empowers enterprises to build next-generation distributed and highly scalable IoT platforms.

IoT Data Management

Common IoT infrastructure can be broken down into three major components: Edge Devices, IoT Hub and Business Insights. Each of those components requires a data management layer.

  • At the Edge, Field Gateways aggregates telemetry data from devices and can apply stream analytics to remove “white noise” or detect anomalies.
  • At the IoT Hub, real-time analytics applied to data streams and cross-correlated with data stores to detect patterns, trends or anomalies.
  • Actionable insights from IoT data drives Business Intelligence, analytics or AI/ML.

DataStax Database platform with Enterprise Analytics and Search can solve data management needs for any IoT Platform at any level and provide always-available, resilient and highly scalable data stores for mission-critical IoT data.

IoT Data Management

Data Flow in Stateful IoT Gateway

Field Gateway can quite often be used for data aggregation and event processing at the edge. With a DataStax Database platform you can create a cluster for data aggregation at the edge that is built to support high-speed data ingestion and store times series data easily. 

Data Flow in Stateful IoT Gateway

Data Processing at the Edge

Managing device operational and telemetry data at a global scale is a very challenging task. DataStax Database platform is distributed at its core, so data replication between Central IoT Data Hubs and Edge clusters couldn’t be easier.

Data Processing at the Edge

IoT Hub Multi-Cloud Geo-Replication

DataStax Database platforms are built on Apache Cassandra™ and uniquely designed to support multi-region deployment. It allows you to expand data layers for any IoT platform across multiple geographies and provide truly masterless, always available and highly scalable modern database platforms that are ready for the exponential growth of IoT data at scale.

IoT Hub Multi-Cloud Geo-Replication

DataStax Solutions for IoT

Modern Database platform for IoT Data at scale

Icon
Blog
Why a Hybrid Cloud Database is Your Key to AI and IoT

Not so very long ago, artificial intelligence (AI) was the stuff of science fiction. AI, at least in the minds of the general public, was relegated to fantastically fantastical sci-fi characters such as: Star Trek’s talking computer (A computer that talks? That’s crazy. Maybe in a couple hundred years…) The class M-3 model B-9 General Utility Non-Theorizing Environmental Control Robot from Lost in Space (Danger, Will Robinson!) C-3PO from Star Wars (“What have you done? I’m backwards, you filthy furball!") The Terminator from The Terminator (“I’ll be back…”) Similarly, the notion of an internet of things (IoT) is also rooted in Sci-Fi fantasy. From Dick Tracy’s ‘smart’ watch to The Jetsons’ autonomous and interconnected household devices, the IoT concept was fantasized long before the term was even coined by Kevin Ashton in 1999. The Hybrid Cloud Future Is Now Though AI and IoT aren’t likely to be abandoned by sci-fi yarn-spinners anytime soon, they no longer exist only within the flickering frames of a movie, or between the covers of a fiction book. AI and IoT have already become integral components of our everyday lives. From mission-critical applications such as completely autonomous airliner autopilots to the slightly-more-whimsical, such as personal assistants like Alexa and Cortana, AI and IoT impact our lives on a daily basis. Worldwide, investments in IoT technology are expected to reach $1.2 trillion by 2022. The consumer industry is expected to lead the way in IoT spending, followed by the insurance and healthcare industry verticals. Similarly, we’re just at the beginning of a massive growth in the implementation of AI technology. Gartner recently reported that the number of companies implementing some form of AI tripled in just the past year. Worldwide spending on AI is predicted to more than quadruple from the period starting in 2017 to 2021. The same report forecasts that three-fourths of all business enterprises will deploy AI technology by 2021. AI and IoT: Two Legs of a Tripod Most enterprises—likely including your company—will be making massive investments in AI and IoT in the coming years. But though tremendous growth is forecast for both AI and IoT separately, the truth is that both are inherently interlinked. AI and IoT enhance and strengthen each other; they supercharge each other for use cases involving massive amounts of high-velocity data. InformationWeek has labeled IoT and AI “Tech’s New BFFs,” and describes the teaming of the two technologies as “… a crucial combination that will shape corporate data strategies for years to come.” Put simply, AI cannot reach its full potential to duplicate human-like decision-making capabilities without the massive amounts of data that can be gathered through IoT’s edge devices. And, correspondingly, the full potential of the IoT is made possible through AI’s decision-making capabilities. Together, AI and IoT form two legs of the tripod upon which the future of information technology rests. But a tripod can’t stand on just two legs. The Third Leg: A Hybrid Cloud Database What is the common fuel that powers both AI and IoT? Data. Without access to massive amounts of data, the teaming of AI and IoT is of little value. But the simple availability of a huge quantum of data isn’t enough. Of equal importance is the speed, reliability, and security with which that data can be accessed. And that brings us to the third leg of this tripod that supports the future (and present) of IT: a hybrid cloud database. Why a hybrid cloud database? Why not simply a database accessed and managed through a single private or public cloud? Because the single-cloud model just cannot unfailingly and consistently provide the speed, reliability, and security that are all essential to AI and IoT. A hybrid cloud database ensures worldwide access to highly responsive data across many geographies. It provides speed, reliability, and security — and it also offers reduced costs and enhanced operational efficiencies as bonuses. A hybrid cloud database provides the active-everywhere capability that is essential to AI and IoT. In fact, hybrid cloud databases offer a wealth of advantages that make them key to the future success of all your company’s applications. There’s No Fiction to This Science… It’s amazing how quickly science fiction can turn into reality. It wasn’t so long ago that concepts such as talking computers and self-driving vehicles seemed like they belonged to the distant future. And now they’re part of everyday life. AI and the IoT have enabled a wealth of here-and-now technologies that, seemingly only yesterday, would have seemed far off. InfoWorld recently listed a few of them: Medical devices that can automatically defibrillate a malfunctioning heart and simultaneously call 911 for help Automated agricultural combines that can detect and avoid hitting a loose animal (and notify the farmer to herd the stray back home) Instantaneous credit card fraud detection On-demand recommendations for consumers (Netflix recommendations, for example) These examples just scratch the surface of what’s available, and, perhaps more importantly, hint at the astounding technological advancements to come. All are made possible with AI, IoT, and — the third leg of the triad supporting the future of information technology — the hybrid cloud database. DataStax and Microsoft Azure: The Hybrid Cloud Database Built for Global Enterprises (white paper) READ NOW

Get the Blog
Icon
eBook
The 5 Things Your Enterprise Needs to Manage IoT Data at Scale

Smartphones, smart cities, smart homes, smart cars—IoT has triggered a data explosion, and not every enterprise is prepared to handle it. Beyond collecting and analyzing the increasing volume of data, organizations must figure out how to manage the velocity of that data, as well as how to integrate it with multiple data sources. And that’s just scratching the surface of the IoT challenge. To extract business value out of this inpouring of data, and to take full advantage of IoT boosted by new 5G technology, IT organizations must consider five key technologies. In this ebook, you’ll learn about these five technologies and their benefits. To continue to develop and scale your IoT-driven applications, your infrastructure needs to be able to handle sensor data at velocity, keep data close to the edge, maintain 100% uptime, and make it easy to extract business value. The insights you’ll discover in this ebook will not only help you prepare your organization for this reality; they’ll also help you take full advantage of IoT data. With the right architecture you can enable a better future for your entire company. Download the ebook today to learn more.

Get the eBook
Icon
Blog
Data at Cloud Scale: How IoT Is Changing Data Management

As IoT-enabled supply chains increase exponentially in the oncoming years, data management specialists are faced with a new challenge: handling IoT data at scale. The speed and velocity of data that will be generated with the adoption of 5G and the use of connected vehicles and devices means there will be dozens of new data points to manage. While the huge gain in data will be valuable to the growth of several industries, it will also be problematic for companies that do not have the IT infrastructure in place to cope with the changes ahead. Here are some ways IoT is changing data management and what organizations can do to prepare for the big transition ahead: New Era of Data Management The rapidly growing number of IoT use cases in the next decade, prompted by 5G mobile data networks, means that some data will require an immediate response and real-time analytics will be critical for managing data in both the short term and long term. From connected cars to connected appliances, organizations of all sizes will have new data management needs. Since very few organizations want to build out and manage their own data centers on the grand scale the new economy will demand, they need to explore other options and create a strategic plan for the future. Handling the Influx of New Data Managing how data enters the organization is critical for an organization that’s growing rapidly and accommodating for new technologies. A cloud database can help organizations that want to be ready for IoT—public cloud services can easily scale to meet growing demand and either hybrid or multi-cloud deployments will be effective solutions for scaling data operations. However, the only way organizations can benefit from moving to a multi-cloud platform is with an integration strategy. This poses some inherent challenges and organizations will need to consider the costs of integration and customization for certain applications. In some cases, applications will need to remain on premises because the costs to customize and move them is just too high. A hybrid application model is still the ideal solution but organizations need to be able to move and replicate data across its architecture quickly to maximize the benefits of this effort. A hybrid cloud database solution can adequately prepare businesses for the big increases in data capacity from IoT adoption and can also duplicate data in real time when managing migrations to new cloud-based applications, without causing any major disruptions or loss of service. Next Steps for Organizations 5G adoption on the grand scale won’t happen for a few years but now is a great time for organizations to start planning their data management strategy and considering integration options. Businesses that are adequately prepared for this transition will have a competitive advantage. Creating systems that support scalability, data availability, and distributed computing will be critical for ensuring all applications run successfully and can accommodate for the larger volumes of incoming data. The Top Data Management Challenges of Hybrid Cloud (white paper) READ NOW

Get the Blog