The introduction of the Internet of Things is causing a re-think of how data analytics takes place, particularly the location of where analytics is done.
To address this challenge, MapR has created a small footprint edition of its Converged Data Platform. The idea is to address the need to capture, process, and analyse data that’s being generated by IoT devices close to the source.
Called MapR Edge, the technology will provide secure local processing, quick aggregation of insights on a global basis, and the ability to push intelligence back to the edge so that businesses can can more value from their IoT devices.
Ted Dunning, chief application architect, MapR Technologies, said: “Our customers have pioneered the use of big data and want to continuously stay ahead of the competition.
“Working in real-time at the edge presents unique challenges and opportunities to digitally transform an organisation. Our customers want to act locally, but learn globally and MapR Edge lets them do that more efficiently, reliably, securely, and with much more impact.”
According to MapR, the Edge technology will provide capabilities such as distributed data aggregation to provide high-speed local processing, bandwidth-awareness that adjusts throughput from the edge to the cloud and/or data centre, and a global data plane that provides a global view of all distributed clusters in a single namespace in order to simplify app development and deployment.
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Additional features include, converged analytics, unified security and a standards-based approach that adhered to standards including POSIX and HDFS API for file access, ANSI SQL for querying, Kafka API for event streams, and HBase and OJAI API for NoSQL database.
MapR says that existing solutions in this area were not designed for seamless, large-scale distributed global processing. The company clearly feels that the global-distribution and real-time synchronisation capabilities of the MapR Converged Data Platform will put its offering at the top of the list for analytics at the edge.
