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EPISODE · Nov 17, 2017 · 37 MIN

Graph Storage, Compression & Analytics

from The public affairs · host Mash - UP FM

This podcast explores how Neo4j can be used to efficiently store, manage, and compress large volumes of IoT data generated by connected devices. It discusses graph-based data modeling, storage optimization techniques, and strategies for handling high-velocity sensor data. Perfect for IoT engineers, data architects, developers, and technology professionals interested in scalable connected-data solutions.

Episode metadata supplied by the publisher feed · Published Nov 17, 2017

What this episode covers

This podcast explores how Neo4j can be used to efficiently store, manage, and compress large volumes of IoT data generated by connected devices. It discusses graph-based data modeling, storage optimization techniques, and strategies for handling high-velocity sensor data. Perfect for IoT engineers, data architects, developers, and technology professionals interested in scalable connected-data solutions.

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Graph Storage, Compression & Analytics

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How long is this episode of The public affairs?

This episode is 37 minutes long.

When was this The public affairs episode published?

This episode was published on November 17, 2017.

What is this episode about?

This podcast explores how Neo4j can be used to efficiently store, manage, and compress large volumes of IoT data generated by connected devices. It discusses graph-based data modeling, storage optimization techniques, and strategies for handling...

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