Imagine your company's data is scattered like puzzle pieces across a giant office, a small warehouse, and a remote delivery truck. Instead of moving all those pieces to one expensive central room, this system lets you analyze them right where they are. It acts like a secure, invisible bridge that keeps data private and saves electricity by not moving heavy files unnecessarily.
Organizations struggle to analyze massive amounts of data generated at the edge due to high energy costs, slow performance, and risks to data privacy when sharing information between partners.
A 'stretched' data lake architecture and a Teadal Node MVP that manages data flows across cloud and edge locations while enforcing privacy rules.
If you are a fleet management provider dealing with massive amounts of sensor data from trucks and warehouses — this project developed a stretched data lake that allows you to analyze data at the edge to improve decision speed and reduce energy costs.
If you are a smart factory operator dealing with strict privacy rules when sharing production data with partners — this project developed a mediatorless federation that enables trusted data exchange without compromising confidentiality.
If you are a utility company dealing with high energy consumption from cloud data processing — this project developed energy-aware data management that optimizes data flows across the computing continuum to lower operational costs.
Based on available project data, specific pricing or licensing costs are not mentioned as this is a Horizon-RIA research project.
Yes, the project is designed for the computing continuum, spanning from edge devices to multi-cloud environments, and has already been tested in 5 active pilots.
Based on available project data, the IP and licensing terms are not specified in the provided summary.
The system provides a shared approach for defining, enforcing, and tracking privacy and confidentiality requirements to ensure data flows are trusted and verifiable.
The technology is built to work across multi-cloud and edge environments using a control plane that exploits owned resources to improve analysis.
The consortium is heavily industry-driven, with 12 industrial partners representing 63% of the group. The presence of 8 SMEs suggests a strong focus on commercial viability and agile implementation, while the 10-country spread indicates a broad European market validation strategy.
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Contact us to find out how to integrate TEADAL's energy-aware data lake technology into your edge computing strategy.
