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ScyllaDB NoSQL for Internet of Things (IoT)

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Increase Speed, Scale, and Efficiency for Growing IoT Workloads

IoT-connected devices now exceed 25 billion globally with approximately 125 new IoT devices connecting to the internet every second. Data being captured by sensors and exchanged across a network is estimated to be 50 times the volume of business data. And global spending on IoT is projected to reach $875B by 2025. Spanning industrial machinery to household appliances, automobiles and airplanes to oil and gas transport, and smart meters to smart cities, the IoT universe is vast and ever expanding.

ScyllaDB databases provide a unique blend of speed, scale and efficiency coupled with flexible NoSQL data modeling to power a diversity of IoT applications, and help make IoT data actionable and in real time.

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Advantages of ScyllaDB NoSQL

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Higher Throughput

Capture, assess and react to billions of interdependent events from IoT devices in real-time.

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Lower Latency

Collect and analyze gigabytes to petabytes of machine data points in milliseconds and with high integrity.

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Performance at Scale

Keep pace with growth in sensors, data volume, and query demands with predictable, linear performance.

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High Availability

Make downtime and data loss a thing of the past, even when migrating from another database.

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Lower Cost

Maximize infrastructure, maintain data flexibility, and minimize overhead for lower TCO.

Proven Results

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Meshify’s Scalability is No Accident

23M Data Points

Servicing the insurance industry, Meshify wireless sensors capture environmental data that’s used to predict and prevent accidents. Meshify overcame SQL database scalability challenges for time-series data with ScyllaDB, and with less infrastructure and operational overhead.

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Augury Sees More in Machines

75% Fewer Breakdowns

By delivering real-time insights and historical analytics about the condition of machines on the manufacturing floor, Augury helps their customers perform the right maintenance at the right time. Hitting database scalability limits, Augury moved to ScyllaDB to deliver millisecond queries of time series data and reduce cost and complexity.

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Nauto Finds Risk in Analytics

25K Collisions Avoided

Nauto provides a real-time AI-powered driver safety and fleet management solution that helps predict, prevent, and reduce high risk events. ScyllaDB is critical to Nauto’s Trip Builder application that captures GPS information from vehicle fleets in the cloud and performs time-series analytics at large scale.

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Cobli Heightens Sense of Driving

40% Reduction in Latency

Cobli is the FleetTech that simplifies and improves fleet management using tracking, routing, expense control and driver analytics. Facing scalability and cost issues, Cobli turned to ScyllaDB to achieve the higher availability and write capacity it needed to handle data volumes of 4K+ packets per second.

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GE Predix Gets Smarter Over Time

80% Node Reduction

GE Predix is an industrial IoT times-series platform that provides data scientists, developers, and control engineers with sensor data from edge devices to analyze workloads. Facing spiraling costs, GE reduced annual operational expenses by hundreds of thousands with ScyllaDB while improving database latency and scalability.

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Mistaway Finds Relief in the Cloud

Zero Downtime

Mistaway manufactures IoT enabled mosquito abatement systems. Wanting to focus on value creation and leave the management of their system to a DBaaS, Mistaway trusted ScyllaDB to solve their previously overwhelming data migration challenges and get to a zero maintenance, low stress solution.

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Related Use Cases

Machine Health & Predictive Maintenance

Monitor sensor data to assess the real-time condition of equipment and when to perform maintenance to avoid failures.

Smart Devices

Capture data from meters, gadgets, wearables, appliances, and other electronic devices that collect and exchange data over a network.

Fleet Monitoring & Logistics

Utilize GPS devices to track and transmit activity of fleets of vehicles or equipment and associated workers.

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