Close-to-the-metal architecture handles millions of OPS with predictable single-digit millisecond latencies.
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Devices, vehicles, and machines are increasingly connected and streaming massive volumes of events and data. By some estimates, the Internet of Things generates 5 quintillion bytes of data each day. To monitor and analyze all this data in real time, IoT platforms need an optimal blend of speed, efficiency and scale, along with flexible data modeling that supports time-series events.
Aggregate sensor data from industrial machinery and enable real-time analytics at scale to target maintenance and upgrades before failures and outages occur.
Run heterogenous operational and analytics workloads in real time against the same dataset in a single distributed datastore.
Minimize loss, damage, and theft with real-time streaming geolocation data, across transportation, healthcare, agriculture, industrial, retail, and consumer markets.
Leverage native time-series data at an industrial scale, with a highly reliable and performant backend database that scales as your data grows.
Track multi-modal movement of goods around the globe, while monitoring storage conditions and ensuring provenance and chain-of-custody.
