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.
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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.
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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. 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.
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Factors such reduced hardware and software requirements resulting in lower cost and higher durability and higher persistence of erasure coded data are likely to drive the market. Along with functions such as latency tolerance and large capacity stores are anticipated to drive the market during the forecast period.
It is anticipated to be used for inactive data; and not dynamic data that's being used by databases or structured applications where response time is crucial. Although, some of the players are working on making erasure coding faster, for all purposes and to have small response times.
Erasure coding is more CPU-demanding as parity calculation is an extensive process and can translate into an increased latency affecting response time. Enhanced latency slows production writes and rebuilds.
Lack of awareness among storage managers and buyers are associated with known RAID techniques which is limiting the adoption of erasure code. Erasure coding consumes time to create the codes and write to disk making it unsuitable for the flash/SSD, where replication is frequent.
Thus, poor response time and higher latency are restricting the market growth. Though, enhanced demand of capacity are anticipated to drive the market.
Market for erasure coding can be segmented on the basis of geographical regions and storage type. On the basis of geographical regions market can be segmented into Europe, North America, Asia Pacific, Latin America and Middle East & Africa.
On the basis of storage, market is segmented into cloud and on-device storage. Adoption of cloud-based erasure coding is increasing quickly due to the growing popularity of cloud based deployment model.
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Major players in the erasure coding market are Actifo, Netapp, Nephos Technologies, Fujitsu, HP Enterprise, Pivot3, Nutanix, Rubrik Inc. and Dell EMC Isilon.
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