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Edge Computing Storage

Edge computing storage refers to the practice of storing and managing data at or near the source of data generation, such as IoT devices, sensors, or local servers, rather than in centralized cloud data centers. This approach reduces latency, bandwidth usage, and dependency on cloud connectivity by processing and storing data locally. It enables real-time analytics, offline operation, and improved data privacy for applications like autonomous vehicles, industrial IoT, and smart cities.

Also known as: Edge Storage, Fog Storage, Distributed Edge Storage, Local Edge Storage, Edge Data Storage
🧊Why learn Edge Computing Storage?

Developers should learn edge computing storage when building applications that require low-latency data processing, operate in bandwidth-constrained environments, or need to function offline, such as in remote industrial sites or mobile scenarios. It is essential for use cases like real-time video analytics, predictive maintenance in manufacturing, and healthcare monitoring devices where immediate data access is critical. This skill helps optimize performance, reduce costs, and enhance reliability in distributed systems.

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