Opensourcer MapR has been granted a patent for technology to reliably herd big data.
The Hadoop flinger claims its architecture would safeguard "against data loss with optimised replication techniques and tolerance for multiple node failures in a cluster."
MapR is using the filing to try to differentiate against rival Hadoop flingers. Hadoop is open source with others using professional services or the addition of enterprise-y extensions to gain an edge over each other.
Anil Gadre, MapR's senior vice president of product management, specifically pointed to the fact it was a patent filed using open source. In a statement, he called this a "great example" of how foundational innovation could be combined with open source so that customers could gain a competitive advantage.
A container in MapR's world is defined as an entity that stores files and directories in its file system.
According to MapR here: "A container always belongs to exactly one volume and can hold namespace information, file chunks, or table chunks for the volume the container belongs to."
The patent specifically covers transactional read-write-update semantics with cluster-wide consistency, it provides recovery techniques that "reconciles the divergence of replicated data after node failure" - even while transactional updates are being added - and it spans techniques that allow "extreme performance and scale while supporting familiar APIs."
MapR filed for the patent on 29 December, 2011, and it was awarded on 8 December 2015.
The company's decision to trumpet the patent comes amidst something of a dearth of patents in the big data world – at least on the open-source side. IBM, owner of the DB2 database and moving on big data, is consistently the industry's biggest holder of patents. MapR described patent 9,207,930 as "adding to a growing IP portfolio", but the firm is on the other end of the IBM scale with this the only patent currently assigned to MapR. ®