Remove Analysis Remove Analytics Remove IoT Remove Latency
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Adding New Capabilities for Real-Time Analytics to Azure IoT

ScaleOut Software

The population of intelligent IoT devices is exploding, and they are generating more telemetry than ever. The Microsoft Azure IoT ecosystem offers a rich set of capabilities for processing IoT telemetry, from its arrival in the cloud through its storage in databases and data lakes.

IoT 52
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How digital experience monitoring helps deliver business observability

Dynatrace

DEM provides an outside-in approach to user monitoring that measures user experience (UX) in real time to ensure applications and services are available, functional, and well-performing across all channels of the digital experience, including web, mobile, and IoT.

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The Need for Real-Time Device Tracking

ScaleOut Software

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. We are increasingly surrounded by intelligent IoT devices, which have become an essential part of our lives and an integral component of business and industrial infrastructures. The list goes on.

IoT 78
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Digital Twins Enable Seamless Use of Edge Computing in IoT

ScaleOut Software

Digital twins are software abstractions that track the behavior of individual devices in IoT applications. Because real-world IoT applications can track thousands of devices or other entities (e.g., In previous blogs , we have explored the power of the digital twin model for stateful stream-processing.

IoT 45
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Digital Twins Enable Seamless Use of Edge Computing in IoT

ScaleOut Software

Digital twins are software abstractions that track the behavior of individual devices in IoT applications. Because real-world IoT applications can track thousands of devices or other entities (e.g., In previous blogs , we have explored the power of the digital twin model for stateful stream-processing.

IoT 40
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Unlocking the Value of Device Data with AWS Greengrass.

All Things Distributed

Some applications may also rely on timely decisions: when maneuvering heavy machinery, an absolute minimum of latency is critical. Local aggregation and filtering of data allows customers to send only high-value data to the cloud for storage and analysis. Law of the Land.

AWS 118
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A one size fits all database doesn't fit anyone

All Things Distributed

Use cases such as gaming, ad tech, and IoT lend themselves particularly well to the key-value data model where the access patterns require low-latency Gets/Puts for known key values. The purpose of DynamoDB is to provide consistent single-digit millisecond latency for any scale of workloads.

Database 167