ScyllaDB NoSQL for Internet of Things (IoT)

Increase Speed, Scale, and Efficiency for Growing IoT Workloads

ScyllaDB’s close-to-the-metal architecture extracts the full computing power of modern infrastructure to deliver higher throughput and lower latency at scale – often at far lower cost. Written from the ground up in C++, ScyllaDB doesn’t suffer from Java overhead and its effects on performance. Data is distributed across clustered servers per CPU core and free from resource sharing operations. Capable of 1M+ operations per second per server, ScyllaDB scales linearly and easily – from gigabytes to petabytes – and without interruption.

Proven Results

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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Technical Advantages of ScyllaDB for IoT Applications

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. IoT-connected devices now exceed 25 billion globally with approximately 125 new devices connecting to the internet every second. The data captured by device sensors is also estimated to be 50 times the volume of business data. IoT applications therefore require a database designed to manage massive quantities of commonly unstructured data, for high rates of  ingestion with immediate data access 24×7, and to readily expand as growth demands.

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 in real time.

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Built for Speed

ScyllaDB offers wide-column NoSQL data modeling, delivering faster reads over key-value and document stores at high volume. Further boosting query speed are shard-aware drivers that connect client requests directly to the exact CPUs within nodes that are responsible for the data.  And ScyllaDB tunes itself automatically to maintain optimal read and write speeds and minimize administrative overhead.

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Extreme Efficiency

ScyllaDB’s write path follows the LSM-tree structure, delivering fast writes at high volume with immediate reads – and is ideal for storing time series data for IoT.  A variety of compaction strategies are designed for different workloads, such as Time-window for time series data, or unique Incremental Compaction that can reduce storage costs by a third. Time to Live automatically deletes expired data to help maximize storage efficiency.

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High Availability

ScyllaDB’s architecture is also highly fault tolerant with no single point of failure.  Data is automatically replicated across multiple nodes with eventual consistency in milliseconds – even between data centers in different geographic regions – to prevent data loss and help ensure round-the-clock application availability.

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