Erasure Coding Market: Overview of key Market Forces Propelling and Restraining Market Growth

Erasure Coding is a parity based protection technique that utilizes fragmentation, expansion and encoding of data and storing it at different storage locations such as disks or storage nodes with configurable number of redundant pieces. The aim of erasure coding is to enable recreation of data by using information about the data that is stored somewhere in the array or in another location. An erasure code offers redundancy by breaking data into smaller fragments and storing them in different locations, allowing for the breakdown of two or more elements. The key is that user can recover the data from any combination of a smaller number of these fragments. Erasure coding is a mechanism used for protecting data in cloud-based services as it enables faster rebuilds for drives and protects data across different nodes, along with single storage system.

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Erasure coding provides better data resilience, and data durability or persistence, implying that it can remain for longer period of time regardless of the media it is being stored on. Erasure coding consumes less storage than mirroring, which doubles the volume of storage required. It offers higher and configurable levels of protection against hardware failure, is suited to very large scale and archival storage  Erasure coding is useful for large quantities of data and applications or systems that need to tolerate failures, such as, data grids, disk array systems, object stores, distributed storage applications and archival storage. Erasure coding is useful for object-based cloud storage with very large volume of cloud storage users.

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Erasure codes are extensively used in data centers since they offer considerably higher reliability than data duplication methods at much lower storage overheads. Erasure coding is use broadly but majorly in large clusters having mission critical data, opting for resiliency. Due to the relatively large number of segments of an object. Erasure coding requires larger number of devices to achieve a desired level of fault-tolerance, hence, it is not useful for small clusters. Erasure coding offers advanced and configurable levels of protection against hardware failure and is suited for large scale and archival storage.