The United States Patent and Trademark Office recognised the detail differentiation of the Hadoop specialist’s work within the free, Java-based programming framework of Hadoop. Though the technology is derived from technology created by the open source oriented Apache Software Foundation, the patent office has judged that MapR’s performance, data protection, disaster recovery and multi-tenancy features merit a recognisable level of differentiation.
The key components of the patent claims include a design based on containers, self-contained autonomous units with their own operating system and app software. Containers can ring fence data against loss, optimise replication techniques and create a system that can cater for multiple node failures in a cluster.
Other vital components of the system are transactional read-write-update semantics with cluster-wide consistency, recovery techniques and update techniques. The recovery features can reconcile the divergence of replicated data after node failure, even while transactional updates are continuously being added. The update techniques allow for extreme variations of performance and scale while supporting familiar application programming interfaces (APIs).
MapR claims its Converged Data Platform allows clients to innovate with open source, provides a foundation for analytics (by converging all the data), creates enterprise grade reliability in one open source platform and makes instant, continuous data processing possible.
It’s the differentiation of the core with standard APIs that makes it stand out from other Apache projects, MapR claims. Meanwhile the system’s ability to use a single cluster, that can handle converged workloads, makes it easier to manage and secure, it claims.
“The patent details how our platform gives us an advantage in the big data market. Some of the most demanding enterprises in the world are solving their business challenges using MapR,” said Anil Gadre, MapR Technologies’ senior VP of product management.